In northern Tunisia, the co-circulation of two related sand fly-borne phleboviruses, Toscana virus (TOSV) and Punique virus (PUNV) was previously demonstrated. In contrast to TOSV, a prominent human pathogen, there is no data supporting that PUNV is capable to infect and cause disease to humans. We studied the respective involvement of TOSV and PUNV in human infections in northern Tunisia through a seroprevalence study.The presence of TOSV and PUNV neutralising antibodies (NT-Ab) was tested in human sera collected from 5 districts of the governorate of Bizerte, and the titres of NT-Ab were estimated by microneutralisation (MN) assay.A total of 1,273 sera were processed. TOSV and PUNV NT-Ab were detected in 522 (41%) and 111 sera (8.72%) respectively. TOSV seroprevalence varied from 17.2% to 59.4% depending on the district. Analysis of TOSV geometric mean titre values demonstrated a constant increase according to the age. The vast majority of sera containing NT-Ab were found to be more reactive toward TOSV than PUNV. Indeed, past infections with PUNV and TOSV were undisputable for 5 and 414 sera, respectively.PUNV may be capable to infect humans but at a low rate. TOSV is responsible for the vast majority of human infections by sand fly-borne phleboviruses in northern Tunisia. TOSV must be considered by physician and tested in diagnostic laboratories for patients with meningitis and unexplained fever in northern Tunisia. In northern Tunisia, two different pheboviruses are known to circulate in sand fly population, Toscana virus (TOSV) and Punique virus (PUNV). In contrast to TOSV, a prominent human pathogen, there is no data supporting that PUNV is capable to infect humans and to cause a disease. We studied the respective involvement of TOSV and PUNV in human infections in northern Tunisia through a seroprevalence study. Because TOSV and PUNV are antigenically and genetically closely related, it is difficult to distinguish between them by using broadly reactive serological tests, such as enzyme-linked immunosorbent assay (ELISA). Thus, we developed a method of microneutralisation assay using the two viruses in a comparative manner. A total of 1,273 sera were processed. We provide first evidence to support (i) that Punique virus may be capable to infect humans but at a low rate, (ii) that TOSV, the most prevalent arbovirus in Southern Europe, is responsible for the vast majority of human infections by sand fly-borne phleboviruses in northern Tunisia. Therefore, it is important to consider TOSV as an important pathogen that needs to be included in all virological diagnostic concerning patients with meningitis and unexplained febrile illness originated from Northern Tunisia. Phlebovirus within the Bunyaviridae family. These sand fly-borne phleboviruses belong to three distinct serocomplexes : (i) the Sandfly fever Naples virus serocomplex including Toscana virus (TOSV) and related viruses , (ii) the Sandfly fever Sicilian virus serocomplex including Sicilian virus and related viruses , and (iii) the Salehabad virus serocomplex including Salehabad virus and related viruses  i.e. between April and October The risk of human infection with sand fly-transmitted viruses has been shown to cover extended geographic areas  because of the presence of the sand fly vectors Phlebovirus is higher than initially suspected Sandfly fever Naples virus. However, there is currently no additional evidence suggesting that PUNV is capable to infect and cause disease to humans. Recently, TOSV was suspected to circulate in Tunisia based on serological study Recent discoveries of new sand fly-borne phleboviruses from Mediterranean countries has indicated that the viral diversity in genus the The objective of the present work was to evaluate and to compare the respective involvement of TOSV and PUNV through a seroprevalence study in human, among a population at risk for sand fly-transmitted diseases originated from Northern Tunisia, by using the two viruses in a comparative manner through a microneutralisation (MN) assay.Sera were collected from February to April, 2011, from out care patients visiting local hospitals for medical reasons that were not available to us and requiring blood analysis. These patients are originated from 5 districts  of the governorate of Bizerte, Northern Tunisia located in the vicinity of the site where TOSV and PUNV were isolated repeatedly from sand flies in 2008, 2009, 2010 Figure 1This study was performed with leftovers of these samples. The tubes were anonymized and only the sex, age and district address were recorded. This study was approved by the ethical committees of the Pasteur Institute of Tunis under the agreement number IPT/UESV/19/2010, and of the Marseille Federation of Research No 48 under the number 13-008.Phlebotomus sp. in Tunisia in 2009 (Strain Tunisie2009T101). The two virus strains were titrated in Vero cells. A volume of 50 µL containing 100 TCID50 was added into each well except for the controls that consisted of PBS. The plate containing 100 TCID50 of virus and the four two-fold dilutions (1∶10 to 1∶80) of serum was incubated at 37°C for one hour. Then, a 50 µL suspension of Vero cells containing approximately 2.105 cells in 5% foetal bovine serum was added to each well, and incubated at 37°C in presence of 5% CO2. After 5 days, the microplates were read under an inverted microscope, and the presence or absence of cytopathic effect was noted. The titre  was recorded.The virus microneutralisation (MN) assay, previously described for phleboviruses The threshold for positivity was defined as 1∶20. Differences in titres lower than four-fold dilutions were considered as not significantly different. Serum exhibiting paired results such as neg/≥1∶20, 1∶10/1∶20, 1∶10/≥1∶40, and 1∶20/≥1∶80 were indicative of a single infection against the virus corresponding to the highest dilution. Serum exhibiting paired results such as neg/1∶10, were considered as negative for both viruses. Serum exhibiting paired results such as 1∶20/1∶40, and 1∶40/1∶80 were indicative of past infection with both viruses.The GMT observed in MN with TOSV and PUNV were calculated respectively. Sera exhibiting an absence of neutralisation were attributed a score of 5. Sera exhibiting neutralising properties were attributed the reciprocal of the dilution . Dilutions ≥1∶160 were not tested since long range analysis (1∶10 to 1∶2560) of 100 randomly sorted sera indicated that titres ≥160 were seldom observed.A total of 1,273 sera  were collected. The median age was 53 years (range: 2–97). They consisted of 86, 484, 244, 240, and 219 sera collected from the districts of Jounine, Mateur, Ras Jabel, Sejenane, and Utique, respectively Figure 1Neutralising antibodies against TOSV (TOSV NT-Ab) were detected in a total of 522 sera (41%): 96 had titre 10, 116 had titre 20, 165 had titre 40, and 145 had titre 80 Table 2.Neutralising antibodies against PUNV (PUNV NT-Ab) were detected in a total of 111 sera (8.72%): 99 had titre 10, 11 had titre 20, 0 had titre 40 and 1 had titre 80 Table 2.Text S1.Results are presented in According to a 1∶20 cut-off for positivity and four-fold dilutions of difference, only five sera .These results suggested that the presence of TOSV NT-Ab may be responsible for PUNV cross-neutralisation. As shown in Detailed results of TOSV are presented globally for the 1,273 sera and for each region individually in GMT analysis by age group is presented in e.g. TOSV, Naples virus and Sicilian virus) are recognised human pathogens In the Mediterranean area, several phleboviruses are circulating as demonstrated by virus isolation and/or molecular detection in sand flies, and some of them  or indirect immunofluorescence assay In Tunisia, PUNV strains have been isolated from To attempt the determination of the respective role of TOSV and PUNV in human infection, a sero-epidemiological study concerning a population living in endemic areas for visceral leishmaniasis originated from Northern Tunisia was performed. A total of 1,273 sera were tested using MN assay, with the two viruses independently. In agreement with other studies e.g., by investigating summertime undetermined febrile illness in the regions where the virus circulates).Our results indicate that PUNV (or closely related antigenic variants) can infect humans, but it occurs seldom in a region where the virus circulates at high level in sand fly populations. It should be underlined that this does mean that PUNV is not capable to cause human disease, but only that it is involved at a much lower rate in human infections than TOSV in this region of Tunisia. The clinical presentation associated with PUNV  in humans is currently unknown. Thus, its possible medical interest deserves further investigations  are much higher than those (2–25%) reported in countries of southern Europe such as Portugal, Spain, France, Italy, Greece and Turkey Analysis of GMT values on the global population demonstrated a constant increase according to the age. Similar result were reported in other studies concerning various populations from endemic countries, where both anti-TOSV seroreactivity and TOSV-specific antibody prevalence increased significantly with age In conclusion, this study conducted in Northern Tunisia showed: (i) TOSV is responsible for the vast majority of human infections by sand fly-borne phleboviruses, (ii) PUNV, a recently discovered sand fly-transmitted phlebovirus that co-circulates with TOSV, is capable of infecting humans but at a low rate, (iii) important variations among seroprevalences are observed depending on the geographic area, and thus on environmental factors, and (iv) TOSV should be considered as an important pathogen and that needs to be included in all virological diagnostic concerning patients with meningitis and unexplained febrile illness originated from Northern Tunisia.Text S1Detailed analysis of (DOC)Click here for additional data file.Checklist S1STROBE Checklist.(DOC)Click here for additional data file.


Diptera are vectors of major human and animal pathogens worldwide, such as dengue, West-Nile or bluetongue viruses. In seasonal environments, vector-borne disease occurrence varies with the seasonal variations of vector abundance. We aimed at understanding how diptera-borne viruses can persist for years under seasonal climates while vectors overwinter, which should stop pathogen transmission during winter. Modeling is a relevant integrative approach for investigating the large panel of persistence mechanisms evidenced through experimental and observational studies on specific biological systems. Inter-seasonal persistence of virus may occur in hosts due to viremia duration, chronic infection, or vertical transmission, in vector resistance stages, and due to a low continuous transmission in winter. Using a generic stochastic modeling framework, we determine the parameter ranges under which virus persistence could occur via these different mechanisms. The parameter ranges vary according to the host demographic regime: for a high host population turnover, persistence increases with the mechanism parameter, whereas for a low turnover, persistence is maximal for an optimal range of parameter. Persistence in hosts due to long viremia duration in a few hosts or due to vertical transmission is an effective strategy for the virus to overwinter. Unexpectedly, a low continuous transmission during winter does not give rise to certain persistence, persistence barely occurring for a low turnover of the susceptible population. We propose a generic framework adaptable to most diptera-borne diseases. This framework allows ones to assess the plausibility of each persistence mechanism in real epidemiological situations and to compare the range of parameter values theoretically allowing persistence with the range of values determined experimentally. The unfolding of the seasons generates profound, cyclical environmental changes, presenting organisms with multiple challenges which are the most difficult and diverse that they must face i) low continuous transmission associated with the survival and residual biting activity of the adult vector, ii) persistence in the host, and iii) persistence in the resistance stages of the vector. Continuous transmission could occur in areas where vectors bite hosts year round; with low winter temperatures lengthening the interval between two meals and the extrinsic incubation period (latency period), clinical cases are rare and may pass unnoticed. This mechanism was suggested to constitute a means of persistence in the Culex/West Nile virus system in southern California Culicoides/bluetongue virus system, cattle present a long viremia and the transmission of the virus from a cow to her calf is possible Culex/Western equine encephalitis virus system, a resurgence of viremia was observed experimentally in snakes after hibernation Hematophagous insects, which have the distinction of being vectors of pathogens that cause disastrous diseases for human and animal health , are no exception to this rule. One of the most striking features of vector-borne diseases is their strong seasonality connected to that of vectors, leading to a quasi-disappearance of clinical cases during the unfavourable season. The pathogens transmitted therefore must develop a persistence strategy to survive the unfavourable season and to adapt to their vectors’ own seasonal dynamics. Conceptually, three independent mechanisms are possible: The existence of each of these mechanisms has been demonstrated, experimentally and by field observations, in different biological systems. In contrast, few studies have investigated several of these pathogen persistence mechanisms, illustrating the difficulty of demonstrating the efficacy of a mechanism and of quantifying its importance under natural conditions Our objective was to assess parameter ranges under which persistence could occur in several virus/vector/vertebrate systems and then to compare the range of parameter values theoretically allowing persistence with the range of values determined experimentally.HP) and a vector population (VP) (HP) is divided into three health states (SH), infectious (IH), and immune (RH). It is assumed to remain constant: the entry rate (Hb) compensates the exit rate (Hm). For our study to be relevant to a wide range of vector-borne diseases, three different demographic regimes of hosts were represented: one with a relatively high turnover adapted to a bird population, a second with an average turnover comparable to that of a ruminant livestock population such as cattle, and a third with a low turnover comparable to a human population.To study these different mechanisms we developed a general common model for all of the mechanisms of virus persistence. Modifications due to each hypothesis are described thereafter. We used a standard compartment model to describe the vector-borne transmission of a pathogen between a vertebrate host population (ion (VP) . The parh states : susceptVP) is divided into three health states (SV), exposed (EV), and infectious (IV). The vectors have a mean lifespan of 1/Vm. In a disease-free environment, the density-dependant growth of this population is regulated by the seasonal carrying capacity K(t). If VP<K(t), susceptible vectors are born, if VP≥K(t), there is excess mortality of vectors in each health state. In a period favourable for vectors, the K function is a sinusoidal function with a maximum h. In an unfavourable period, the K function is assumed constant and equal to Nb. These Nb vectors are not taken into account in the virus transmission dynamic in this general model, but represent the number of new vectors emerging when the favourable period returns. The vector-borne transmission takes place when an infectious vector (IV) bites a susceptible host (SH) which then becomes infectious (IH), or when a susceptible vector (SV) bites an infectious host (IH) and then becomes exposed but not yet infectious (EV). The dynamics of hosts and vectors are described by the following ODE system (Eq. (1)):In the presence of a virus, the vector population  was transformed into a transition probability . Then, the number of transitions between two given health statuses at time t was represented by a random variable and followed a Binomial distribution, which parameters were the population size in the status concerned and the associated transition probability. For example, for two theoretical health statuses  and associated transition probability p(XY), we would have:The stochastic version of the ODE model was developed to enable us to study persistence phenomena, based on random events. Each transition rate of the ODE (Only the equation regulating vector population birth follows a Poisson probability distribution with parameter The probability of virus persistence 5 years after virus introduction (named hereafter persistence) and the distribution of the extinction dates allowed us to describe the virus capacity to persist over unfavourable periods. Persistence is estimated by the proportion of repetitions in which the virus is still present (either in the host or in the vector populations) 5 years after its introduction. The extinction dates for each repetition correspond to the date when the virus has disappeared from both populations (hosts and vectors). These dates allow the calculation of the proportion of repetitions in which the virus has disappeared per year since the virus introduction. Simulations were carried out over 5 years and not less to study the persistence of the virus and not its invasion capacity.To explore each persistence mechanism, we modified the general model by successively changing one or several features. For each mechanism, we studied the virus persistence and the distribution of extinction dates 5 years after its introduction. We assessed parameter ranges under which persistence could occur according to the host demographic regime.The duration of viremia, meaning the period during which the virus is present in the blood, has been relatively well documented, although the period during which viremia is sufficient to infect vectors is understood less well. Viremia can be extremely variable between individuals in the same population; for example, the viremia of bluetongue virus infection in cattle ranges from 7 to 63 days x] (x being greater than the duration of the unfavourable period (365-d) (M (i.e. the distribution function mode), which is generally short, and the cumulative probability to have a viremia duration longer than (365-d), A  . Two oth (365-d) : the mos65-d), A .On the interval of tested values , we asseIt has long been known that certain arboviruses can be rediscovered in a host weeks or even months after infection, even in the case of brief viremia CIH), was added to the shared model and the equations for hosts (Eq.1) were modified as follows:To represent this mechanism, a fourth host health state , chronicIH), once their viremia ends at rate Iα, either will be chronically infected (CIH) with probability If, or will be cured (RH) I), chronically infected hosts (CIH) can become viraemic again (IH), with occurrence rate p. Independently, they exit the CIH compartment at rate ICα. In the stochastic version of the model, these transitions follow binomial probability distributions.In this way, infectious hosts  are divided into two categories according to whether vertical transmission is possible (with a probability Hg) or not, vertical transmission only being possible during gestation (probability Hb). Infectious individuals for which there is vertical transmission are distributed at infection uniformly over the gestation stages. In the stochastic version of the model, these transitions follow binomial probability distributions.Infectious hosts , the probability of transovarian transmission (Vg) and the total number of individuals entering diapause (dNb). These parameters determine the share of infectious vectors whose offspring will be infectious, and therefore the proportion of infectious vectors among those emerging in the following favourable period. In the stochastic version of the model, these transitions follow binomial probability distributions.These mechanisms are driven by the length of the favourable period during which the vertical transmission is present  managing the seasonality is unchanged but the vectors present in constant numbers (Nb) during the unfavourable period now are involved in the virus spread dynamics (unfNb). These unfNb vectors are distributed in the different health states in proportions equal to those at the end of the favourable period , with a higher increase for a faster renewal of the host population  up to a threshold of 10−3 at which it reaches certainty. After this point, persistence decreases if the duration of chronic infection is long (1/ICα >3 months) and the probability of a return to a viraemic stage is low (p<10−2) (If = 10−3) with an increase of early extinction dates after this value.Regardless of the host demographic regime, persistence increases with the probability of chronic infection (p<10−2) . Hence, p<10−2)  confirmsHg), the relation depending on the host demographic regime (Hg) up to the threshold H = g10−2, progressively diminishing thereafter. For cattle, persistence increases with Hg. It is constant and equal to 1 as soon as Hg >0.5×10−3, with the exception of Hg values between 10−3 and 10−2 , the number of vectors (dNb) and the length of the period over which the population of infected vectors entering diapause (inter) is calculated, the relation depending on the host demographic regime (inter = [1: 243]), persistence doubles when dNb is multiplied by 5, (inter = [230: 243]), persistence decreases as soon as Vg >0.1 for cattle and humans if d = Nb50 000 , the relation depending on the host demographic regime (unfn) and in the duration of the extrinsic incubation period (unf1/q) do not modify persistence.Persistence varies non-linearly with the survival of the vector in winter (1-c regime . In contVunfm >0.967) and 40 days (1-Vunfm >0.975), then diminishes for higher survival durations . However, the existence of such a phenomenon has only been demonstrated for the Culex/reptiles/Western equine encephalitis virus system The persistence mechanism of the virus in the host can ensure, for certain parameter values, virus persistence. In the cattle/bluetongue virus system, long viremia, lasting 7 to 63 days and exceptionally more, could be observed Aedes/dengue virus system, where vertical transmission is about 4% Culex/West Nile virus system, where it is 7 to 8‰ The persistence of the virus in the vector’s overwintering stages reflects the adaptation of these arboviruses to the insects’ diapause mechanisms −1); it is the possible survival of infected vectors that intervenes. It was demonstrated that in the Culex/West Nile virus system, females infected orally could conserve the virus at an undetectable level for 30 to 40 days at 10°C, and become infectious again as soon as the temperature increased Culex females do not usually feed blood and are therefore less likely to be infected, whereas bloodfed females are unlikely to enter diapause and survive winter, their average lifespan in laboratories being 20 days vs. 180 days for overwintering females Culicoides because it is possible to capture small quantities of these insects all winter long without being able to estimate their age Persistence being the same whatever the extrinsic incubation rate and the biting rate, a low continuous transmission does not seem to allow persistence (maximum values tested of 100 days and 1/100 daysCulex and Aedes ones, effectively are involved in the transmission of the Ross River and Rift Valley viruses, which may allow arboviruses to combine the persistence effects in each of these vectors Other persistence hypotheses exist that require more complex approaches to be taken into account. A multiplicity of hosts and/or of vectors may allow virus persistence past the unfavourable season Our modelling approach allowed different arbovirus persistence mechanisms to be investigated. The survival of viruses within a host during the unfavourable season seems to be an effective strategy to adapt to seasonal variations and population dynamics of their vectors, either through extended viremia in a few individuals or through vertical transmission. The reactivation of chronic infections seems rare in arboviruses, although it is conventionally described for parasites, as in the case of malaria. Arboviruses with only a short presence in their hosts could persist through vertical transmission as seems likely for the dengue virus in humans. For viruses such as the West Nile virus, only new experimental investigations may allow overwintering modalities to be specified. Such investigations must aim to demonstrate a possible reactivation of chronic infection, which may be delicate given that a low occurrence can allow persistence, and explore abundances and survival of vectors during winter.


Bunyaviridae infect a wide range of plant, insect, and animal hosts. Tick-borne bunyaviruses in the Phlebovirus genus, including Severe Fever with Thrombocytopenia Syndrome virus (SFTSV) in China, Heartland virus (HRTV) in the United States, and Bhanja virus in Eurasia and Africa have been associated with acute febrile illness in humans. Here we sought to characterize the growth characteristics and genome of Lone Star virus (LSV), an unclassified bunyavirus originally isolated from the lone star tick Amblyomma americanum. LSV was able to infect both human (HeLa) and monkey (Vero) cells. Cytopathic effects were seen within 72 h in both cell lines; vacuolization was observed in infected Vero, but not HeLa, cells. Viral culture supernatants were examined by unbiased deep sequencing and analysis using an in-house developed rapid computational pipeline for viral discovery, which definitively identified LSV as a phlebovirus. De novo assembly of the full genome revealed that LSV is highly divergent, sharing <61% overall amino acid identity with any other bunyavirus. Despite this sequence diversity, LSV was found by phylogenetic analysis to be part of a well-supported clade that includes members of the Bhanja group viruses, which are most closely related to SFSTV/HRTV. The genome sequencing of LSV is a critical first step in developing diagnostic tools to determine the risk of arbovirus transmission by A. americanum, a tick of growing importance given its expanding geographic range and competence as a disease vector. This study also underscores the power of deep sequencing analysis in rapidly identifying and sequencing the genomes of viruses of potential clinical and public health significance.Viruses in the family  Bunyaviridae is the largest family of viruses, with over 350 species that infect a broad range of hosts including plants, arthropods, and vertebrate animals Bunyaviridae family is comprised of five genera: Nairovirus, Bunyavirus, Hantavirus, Phlebovirus, and TospovirusPhlebovirus genus, named Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV), was reported as the cause of an outbreak of severe febrile illness in China Anaplasma phagocytophilum. However, two research groups independently discovered a novel phlebovirus as the cause of SFTS Haemaphysalis longicornis, as the vector of SFTSV In 2011, a new bunyavirus in the Amblyomma americanumA. americanum tick has been associated with an illness of unknown etiology called Southern Tick-borne Rash Illness (STARI) In light of these studies, which have augmented interest in phleboviruses as potential agents of human disease, we sought to sequence the genome of the Lone Star virus (LSV), an unclassified bunyavirus virus originally isolated from the lone star tick, de novo assembly to recover the highly divergent genome of LSV at >1,000-fold average coverage. We show that it is indeed a phlebovirus in the Bunyaviridae family and that it readily infects human and monkey cell lines in vitro.Here we used next-generation sequencing coupled with 6 PFU/ml and 1.2×106 PFU/ml, respectively.Lone Star virus (LSV) induced cytopathic effect (CPE) in both non-human primate (Vero) and human (HeLa) cell types at 72 hours post-inoculation (hpi) . Nearly Bunyaviridae family, reads from which comprised 92.2% of the viral deep sequencing hits. The phlebovirus reads represented all 3 segments and were highly divergent, sharing <50% identity with any other bunyavirus sequence in GenBank. As the alignable reads represented less than 50% overall coverage of the genome , this material was pooled with RNA from a second extraction without nuclease treatment for cDNA deep sequencing library preparation. The final count of raw deep sequencing reads was 15,134,328 total sequences . Using a rapid computational pipeline developed in-house for pathogen identification from deep sequencing data , the dataset was comprehensively analyzed for viruses within 2 h using a single 64-core computational server with 512 GB RAM. First, NGS reads were sequentially preprocessed, aligned to a reference human database, and aligned to a reference bacterial database, with removal of 50.3% , 15.5% , and 1.9% , respectively, of the raw sequences in the dataset. The remaining 4,888,695 sequences, comprising 32.3% of the original dataset, were then aligned to reference viral nucleotide and protein databases to identify reads corresponding to viruses . Among te genome , the fulsegments . Subsequsegments . The mapsegments .Phlebovirus genus, and part of a well-supported clade containing the recently sequenced Bhanja and Palma viruses  . These s viruses , “SFTS” Bunyaviridae family, with the notable exception of the 5′ end of the S segment, which contains a “5′-ACACAGAG” sequence. This deviation from absolute conservation of the terminal signature sequences is also seen in other tick-borne phleboviruses, including SFTS, Heartland, Bhanja, and Palma viruses The termini of the L, M, and S segments of LSV retain the conserved “5-ACACAAAG” and “CUUUGUGU-3” inverted signature sequences common to phleboviruses in the A. americanum tick is well-suited as a zoonotic disease vector because it feeds on a wide assortment of wild animal hosts as well as humans. It is a known vector for the pathogenic agents of Rocky Mountain spotted fever (Rickettsia rickettsia), human monocytic ehrlichiosis (Ehrlichia chaffeensis), and tularemia (Francisella tularensis), and has also been associated with Southern Tick-borne Rash Illness (STARI), for which no etiologic agent has been identified A. americanum is expanding northward in the eastern United States and it has a propensity for biting humans A. americanum to harbor viruses is not well understood. The sequencing of LSV is thus a critical first step in determining the risk of arbovirus transmission by A. americanum.Phleboviruses that are pathogenic to humans can be transmitted by mosquitoes, sand flies, and ticks Our study found that LSV is a member of the Bhanja clade of tick-borne phleboviruses  [10], whin vivo. However, although CPE was observed in both HeLa and Vero cells starting at 72 hpi, the appearance and progression of the CPE was different between the two LSV-inoculated cell lines. In particular, vacuoles were observed only in Vero cells. Similarly, cellular vacuoles presumably containing infectious viral particles were also seen with SFSTV and Heartland virus, which also grow efficiently in Vero cells In this study, both human (HeLa) and monkey (Vero) cells were found to support infection by LSV, suggesting that LSV may be capable of infecting human and other nonhuman primates de novo is challenging for widely divergent sequences such as those found in novel emerging viruses. When related genomes in large sequence databases such as GenBank are lacking, routine algorithms to map/align reads to reference sequences are inadequate. To address these challenges, we have developed a computational pipeline for rapid identification and de novo genome assembly of viral pathogens from deep sequencing metagenomic datasets . After preprocessing and removal of sequences corresponding to host background and/or laboratory contamination, this pipeline incorporates both nucleotide and amino acid alignments to reference databases using efficient and highly parallelizable algorithms to comprehensively identify both known and novel viruses within hours. Protein alignments are critical for detecting highly divergent viruses such as LSV, as shown by the detection of ∼414X the number of phlebovirus reads by amino acid rather than nucleotide alignments . Experiments using LSV were performed in Biosafety Level-2 (BSL-2) facilities certified by the Institutional Biohazards Committees of the CDC and UCSF.Lone Star virus strain TMA 1381 was obtained from the arbovirus reference collection of the Division of Vector-borne Diseases, Centers for Disease Control and Prevention, Fort Collins, CO. This virus was originally submitted to the CDC arbovirus catalog by Robert Kokernot  in 1984  supplemented with 2% FBS . The multiplicity of infection was 1.3 pfu/cell. Cytopathic effect (CPE) was monitored at 24-hour intervals for 7 days. Viral titers were determined at 72 hours post-inoculation (hpi) using a plaque assay. Briefly, cell supernatant was diluted ten-fold and 100 µl was inoculated onto Vero cell monolayers in 6-well plates using a 0.5% agarose double overlay. The cells were visualized with neutral red added to the second overlay.LSV-infected Vero cell cultures were extracted using two different protocols, one to purify RNA from viral particles (“virus purification protocol”) and the other to extract total RNA. First, 130 µL of viral culture supernatant was treated with Turbo DNase, Baseline Zero DNase, Benzonase, and RNase A , and then extracted with the QIAamp UltraSens Virus Kit . A second RNA extraction without pre-nuclease treatment was performed on 400 µL of supernatant using TRIzol reagent . Each extraction was performed according to the manufacturer’s protocol.An LSV cDNA library for Illumina sequencing was prepared with the ScriptSeq version 2 kit according to the manufacturer’s protocol . The input consisted of 30 ng of RNA from the first extraction and 80 ng from the second extraction. RNA was reverse-transcribed to cDNA, adaptors were ligated to the cDNA ends, and the cDNA was then amplified with 17 cycles of PCR. AMPure XP beads  were used to remove primer and adaptor dimers as well as larger PCR fragments (>600 bp) from the amplified cDNA library. Library size distribution and concentration were determined using a High Sensitivity DNA kit on an Agilent Bioanalyzer 2100 instrument  and a KAPA Library Quantification Kit , respectively. Approximately 10 pmol of library was used for 150-bp paired-end sequencing on an Illumina MiSeq Sequencer .−1 for RAPSearch) to identify viral sequences. For these initial alignments, the advantage of SNAP and RAPSearch was a 10–1,000X increase in computational speed while maintaining comparable accuracy relative to existing algorithms such as BLASTn/BLASTx −8. The approximate computational times for the preprocessing, SNAP nucleotide alignment to human/bacterial/viral databases, and RAPSearch amino acid alignment to the viral protein database were 5 minutes, 10 minutes, and 135 minutes, respectively .All computational analyses of deep sequencing data were performed on a 64-core 1 U Quad AMD Opteron 6200 computational server with 512 GB RAM and using the Ubuntu 12.04 LTS operating system. Raw deep sequencing reads were first “preprocessed” by trimming of primers, filtering to exclude low-quality and low-complexity sequences, and removing all residual sequences <50 bp in length de novo contig assembly using the entire preprocessed dataset was performed using the PRICE assembler  After running the deep sequencing reads through the computational pipeline, analysis of a subset of reads identified LSV as a highly divergent bunyavirus . CoveragPhylogenetic analysis was performed on the 4 bunyavirus proteins: RdRp (L segment), glycoprotein (M segment), N protein (S segment), and NSs protein (S segment). Multiple sequence alignments of each of the LSV proteins relative to the corresponding protein from nearly all available phlebovirus sequences in GenBank and from Gouleako virus Deduced amino acid sequences of LSV were compared by pairwise sliding window alignments in Geneious RdRp (L segment): Aguacate virus (NC_015451), Armero virus (HQ661805), Bhanja virus strain ibAr2709 (JX961616), Bhanja virus strain IG690 (JX961619), Bhanja virus strain M3811 (JQ956376), Bhanja virus strain R-1819 (JX961622), Candiru virus (NC_015374), CCHF virus (NC_005301), EgAN 1825-61 virus (HM566159), Gouleako virus (HQ541738), Heartland virus (JX005847), Massilia virus (EU725771), Palma virus strain PoTi4.92 (JX961628), Palma virus strain M3443 (JQ956379), Precarious point virus (HM566181), Rift Valley fever strain Sharqiya (NC_014397), Rift Valley fever virus strain Smithburn (DQ375430), Salobo virus (HM627185), Tosacana virus (NC_006319), Sandfly fever Turkey virus (NC_015412), SFTS virus BX-2010 (JF682773), SFTS virus HB29 (NC_018136), SFTS virus HN6 (HQ141595), Uukuniemi virus (UUKLRNAP), Zaliv Terpeniya virus (HMX66191); glycoprotein (M segment): Aguacate virus (NC_015450), Armero virus (HQ661806), Bhanja virus strain ibAr2709 (JX961616), Bhanja virus strain IG690 (JX961620), Bhanja virus strain M3811 (JQ956377), Bhanja virus strain R-1819 (JX961620), Candiru virus (NC_015373), EgAN 1825-61 virus (HM566158), CCHF virus (NC_005300), Gouleako virus (HQ541737), Heartland virus (JX005845), Massilia virus (EU725772), Palma virus strain PoTi4.92 (JX961629), Palma virus strain M3443 (JQ956380), Precarious point virus (HM566179), Rift Valley fever strain Sharqiya (NC_014396), Rift Valley fever virus strain Smithburn (DQ80193), Salobo virus (HM627183), Tosacana virus (NC_006320), Sandfly fever Turkey virus (NC_015411), SFTS virus BX-2010 (JF682774), SFTS virus HB29 (NC_018138), SFTS virus HN6 (HQ141596), Uukuniemi virus (UUKGPM), Zaliv Terpeniya virus (HMX66193); N (S segment): Aguacate virus (NC_015452), Armero virus (HQ661807), Bhanja virus strain ibAr2709 (JX961618), Bhanja virus strain IG690 (JX961621), Bhanja virus strain M3811 (JQ956378), Bhanja virus strain R-1819 (JX961624), Candiru virus (NC_015375), CCHF virus (NC_005302), EgAN 1825-61 virus (HM566160), Gouleako virus (HQ541736), Heartland virus (JX005843), Massilia virus (EU725773), Palma virus strain PoTi4.92 (JX961630), Palma virus strain M3443 (JQ956381), Precarious point virus (HM566180), Rift Valley fever strain Sharqiya (NC_014396), Rift Valley fever virus strain Smithburn (DQ80157), Salobo virus (HM627184), Tosacana virus (NC_006318), Sandfly fever Turkey virus (NC_015413), SFTS virus BX-2010 (JF682775), SFTS virus HB29 (NC_018137), SFTS virus HN6 (HQ141597), Uukuniemi virus (UUKNNSA), Zaliv Terpeniya virus (HMX66192); NSs (S segment): Aguacate virus (NC_015452), Armero virus (HQ661807), Bhanja virus strain ibAr2709 (JX961618), Bhanja virus strain IG690 (JX961621), Bhanja virus strain M3811 (JQ956378), Bhanja virus strain R-1819 (JX961624), Candiru virus (NC_015375), EgAN 1825-61 virus (HM566160), Heartland virus (JX005843), Massilia virus (EU725773), Palma virus strain PoTi4.92 (JX961630), Palma virus strain M3443 (JQ956381), Precarious point virus (HM566180), Rift Valley fever strain Sharqiya (NC_014396), Rift Valley fever virus strain Smithburn (DQ80157), Salobo virus (HM627184), Tosacana virus (NC_006318), Sandfly fever Turkey virus (NC_015413), SFTS virus BX-2010 (JF682775), SFTS virus HB29 (NC_018137), SFTS virus HN6 (HQ141597), Uukuniemi virus (UUKNNSA), Zaliv Terpeniya virus (HMX66192).Genbank accession numbers used for The complete genome sequence of LSV has been submitted to GenBank (GenBank accession numbers KC589005-KC589007). Deep sequencing reads have been submitted to the NCBI Sequence Read Archive (GenBank accession number SRP018532).


Sclerotinia sclerotiorum, is one of the most important diseases of pea (Pisum sativum L.), however, little is known about the genetics and biochemistry of this interaction. Identification of genes underlying resistance in the host or pathogenicity and virulence factors in the pathogen will increase our knowledge of the pea-S. sclerotiorum interaction and facilitate the introgression of new resistance genes into commercial pea varieties. Although the S. sclerotiorum genome sequence is available, no pea genome is available, due in part to its large genome size (~3500 Mb) and extensive repeated motifs. Here we present an EST data set specific to the interaction between S. sclerotiorum and pea, and a method to distinguish pathogen and host sequences without a species-specific reference genome.White mold, caused by de novo assembly of 128,720 high-quality reads generated by 454 pyrosequencing of the pea-S. sclerotiorum interactome. A method based on the tBLASTx program was modified to distinguish pea and S. sclerotiorum ESTs. To test this strategy, a mixture of known ESTs  from public databases were pooled and parsed; the tBLASTx method successfully separated 90.1% of the artificial EST mix with 99.9% accuracy. The tBLASTx method successfully parsed 89.4% of the 454-derived EST contigs, as validated by PCR, into pea  and S. sclerotiorum  categories. Two thousand eight hundred and forty pea ESTs and 996 S. sclerotiorum ESTs were predicted to be expressed specifically during the pea-S. sclerotiorum interaction as determined by homology search against 81,449 pea ESTs  and 57,751 S. sclerotiorum ESTs . Among those ESTs specifically expressed, 277 (9.8%) pea ESTs were predicted to be involved in plant defense and response to biotic or abiotic stress, and 93 (9.3%) S. sclerotiorum ESTs were predicted to be involved in pathogenicity/virulence. Additionally, 142 S. sclerotiorum ESTs were identified as secretory/signal peptides of which only 21 were previously reported.10,158 contigs were obtained by S. sclerotiorum interaction. Additionally, the tBLASTx method used to parse S. sclerotiorum and pea ESTs was demonstrated to be a reliable and accurate method to distinguish ESTs without a reference genome.We present and characterize an EST resource specific to the pea- Sclerotinia sclerotiorum (Lib.) de Bary, is a devastating disease of over 400 reported dicotyledonous hosts [Pisum sativum L.) under the appropriate environmental conditions [White mold, caused by us hosts . The disnditions . Currentnditions , only paS. sclerotiorum pathogenicity and resistance in pea would increase our knowledge of the pea-S. sclerotiorum interaction and facilitate the introgression of resistance into pea varieties. However, progress in these areas has been hampered by the lack of sequence information regarding the pea genome. Although other legume genomes, including the models Medicago truncatula, Lotus japonicus and economically important Glycine max (soybean) are available [Pisum sativum is still genome resource-poor in part due to the large genome size and large fraction of highly repetitive DNA [The identification of genes underlying vailable , Pisum stive DNA .S. sclerotiorum interaction obtained by 454 pyrosequencing and propose a method of rapid and efficient transcriptome characterization in a non-model species with little prior molecular information. We also report on the development and validation of a strategy to distinguish plant and fungal ESTs using the tBLASTx program and “proxy-reference” genomes in the absence of true reference genomes.The performance of Next-Generation sequencing (NGS) technologies continue to rise while costs continue to fall which enables researchers to conduct whole transcriptome sequencing (RNAseq) studies of interactions between plants and pathogenic fungi . The appde novo assembly of 128,720 high-quality reads produced on a Roche 454 GS FLX sequencer  revealed that 46 contigs showed significant alignment with the proxy plant genome database, 43 showed significant alignment with the fungal genome database and 40 showed significant alignment with both databases, 2 contigs showed significant alignment only with virus genomes. By comparing the e-value ratio (virus/fungi or virus/plant) of all proxy-reference genome alignments, 10 contigs were assigned to pea and 9 contigs were assigned to S. sclerotiorum based on an e-value ratio >1e20, 30 contigs were difficult to distinguish, with e-value ratios between 1e-20 and 1e20. BLASTn analysis of the 32 unassigned contigs against pea and S. sclerotiorum ESTs from known sources revealed that 20 contigs, including the 2 that only aligned with virus genomes, had high identity matches to pea with 95% accuracy and 95% query coverage, and 1 to S. sclerotiorum. The 11 contigs which were difficult to assign to a genome database by either tBLASTx or BLASTn methods were far more similar to plant or fungi than to virus genomes.The tBLASTx program identified 51 contigs with a BLAST hit  to virus or viroid DNA with an e-value cutoff threshold of less than 1eS. sclerotiorum ESTs were downloaded from GenBank to test the tBLASTx sorting method. Three hundred twenty-one ESTs with vector contamination and 71 ESTs highly similar to virus or viroids were removed from the total pool of 36,080 known pea and S. sclerotiorum ESTs. Using an e-value threshold of 1e-3, 35,688 mixed ESTs from pea and S. sclerotiorum were compared to legume and fungal proxy-reference genome databases and parsed using the tBLASTx program , 355 S. sclerotiorum ESTs  and 1,075 that were ambiguous . This brought the number of classified ESTs for each category to 5,067 for pea, 2,659 for S. sclerotiorum, 1,075 as ambiguous with high matches to both proxy-reference genomes, and 1,357 with no significant alignment. The remaining 2,432 EST contigs that were ambiguous or showed no significant alignment were further parsed with BLASTn analysis against known pea and S. sclerotiorum ESTs if identity and query coverage were both equal to or greater than 95%. 1,232 ESTs of this pool were assigned with BLASTn to pea and 121 ESTs were assigned to S. sclerotiorum, leaving 310 ambiguous and 769 EST contigs with no significant alignment. In total with tBLASTx and BLASTn, 10,158 contigs were separated into 6,299 pea ESTs, 2,780 S. sclerotiorum ESTs, 310 ambiguous ESTs and 769 unassigned ESTs . Of these, 1,784 ESTs matched with an e-value cutoff of 1e-10, in which 294 ESTs matched with 95% identity for 95% of more of the query length to the S. sclerotiorum EST growth libraries. Of the remaining 996 unique ESTs, it was possible to annotate 438 ESTs of which 95 ESTs were described as being related to pathogen virulence or pathogenicity  method predicted 244 secretory signals, and the Hidden Markov Model (HMM) predicted 216. A total of 142 ESTs were identified by both NN and HMM and can be considered putative secretory peptides with high confidence  is the method of choice in non-model systems for transcript discovery and genome annotation [S. sclerotiorum ESTs we demonstrated that Roche 454-pyrosequencing is a useful technique to characterize the host-pathogen interactome when genome resources are limited.Despite  species . By sequnotation . HoweverCoffea arabicaHemileia vastatrix interaction no validation of the method was presented [Two different strategies have been utilized previously to identify transcript origins in mixed plant and fungal EST datasets. One is a predictive method based on triplet nucleotide usage frequencies  and the resented .S. sclerotiorum to distinguish mixed transcripts. Using an artificial mixture of known pea and Sclerotinia ESTs, we found the error rate using the BLAST method was significantly lower than the triplet nucleotide frequencies method (Table S. sclerotiorum (strain 1980) has been sequenced [S. sclerotiorum genome  used in test data, which may result in no significant alignment against the proxy-reference plant or fungal genome databases, particularly when non-coding mRNA is considered. The remaining unassigned EST contigs (21%) were parsed using BLASTn searches against known pea and S. sclerotiorum ESTs, which assigned 44.4% of the unassigned contigs. Using this combined tBLASTx and BLASTn approach 89.4% of the 10,158 contigs were identified as pea  or S. sclerotiorum EST . Additionally, the EST parsing method was validated by PCR demonstrating that the parsing method was able to correctly assign ESTs from the 454 data set with a low error rate.Classification of genes from a pool of mixed cDNA by traditional sequence similarity analysis (BLAST) is of interest to many investigations into plant-pathogen interactions. DNA sequencing is becoming more affordable and whole genome sequences of many organisms are becoming available and will aid in plant-pathogen interaction studies. However, in pea these resources are not available, therefore, we used a standalone BLAST approach against proxy-reference genome databases with high genetic similarity to pea or od Table . We alsood Table . In addiequenced , there aS. sclerotiorum interactome were defined and identified by comparing EST contigs in our library against those of non-interaction EST libraries of pea and S. sclerotiorum. Although we identified a total of 2,840 (45.1%) putatively unique pea ESTs it was only possible to annotate 1,631 of these and only 451 had annotations suggesting roles in defense or response to biotic and abiotic stress. Most of the annotated genes are consistent with previous expression profiling analyses in Brassica napus infected with Sclerotinia sclerotiorum[In response to pathogen attack, plants have evolved complex signaling and defense pathways. Putatively unique ESTs in our pea-erotiorum. FollowiP. syringae in Arabidopsis [Transcriptional control of the expression of stress-responsive genes is a crucial part of plant response to a range of abiotic and biotic stresses . We demobidopsis .Sclerotinia sclerotiorum[Plant defenses are regulated through a complex network of transduction pathways . Sixty-nerotiorum,21.Expression of downstream proteins, including defense-associated proteins, was induced through signal transduction and transcription factor regulation after pathogen infection. In this study, 82 unique pea ESTs encoding defense related proteins were detected Table . Four coS. sclerotiorum contigs as specifically expressed during pea-S. sclerotiorum interaction through comparison of EST contigs against S. sclerotiorum ESTs from growth libraries. Ninety-five of 438 annotated contigs were described as being involved in pathogen virulence or pathogenicity  with white mold disease symptoms and stored as air dry sclerotia at room temperature. Isolate WMA-1 (=ATCC MYA-4521) was demonstrated to be genetically representative of eight S. sclerotiorum strains sampled from legume hosts from various geographic locations using randomly amplified polymorphic DNA (RAPD) analysis . Plants were inoculated with a 5 mm plug collected from the leading edge of an actively growing colony on a potato dextrose agar (PDA). The plug was placed fungal side down on the stem between the 4th and 5th detectable nodes and held in place by wrapping with Parafilm. Plants were transferred to a growth chamber with a 12 h photoperiod, an approximate 60% relative humidity, temperature of 20 ± 1°C and a 12 h photoperiod, for 72 hours to allow disease lesion development prior to RNA extraction.Three plants of pea cultivar ‘Lifter’ (PI628276) were established per 1 gallon plastic pot in Sunshine LA 4 potting mix . The plants were maintained in a greenhouse for 4 weeks with supplemental lighting extending the day length to approximately 14 h (October). Day and night temperatures were 22 ± 2°C and 16 ± 2°C, respectively. A 1 cm stem section was collected from each of 18 infected plants by cutting above and below the lesion front advancing toward the base of the plant. The stem section included both necrotic and green tissue with the advancing lesion front located in the center of the section. Stem sections were snap-frozen in liquid nitrogen and ground to a fine powder with a mortar and pestle. A total of 3 ml of TRIzol  was added to the ground tissue and the sample was split in half for column purification with the TRIzol Plus RNA purification kit . The additional step of on-column DNA digestion was performed with DNase I  to remove contaminating DNA. RNA was eluted in 250 μl of water per spin column. Poly-A RNA was isolated from total RNA with the Oligotex kit using the mRNA spin-column protocol . Purified mRNA was eluted in a total of 100 μl of 5 mM Tris (pH 7.5). RNA and mRNA quantity was determined with a spectrophotometer . Total RNA and mRNA quality was assessed with an RNA Nano LabChip on an Agilent 2100 Bioanalyzer .Purified mRNA was used to construct a full length normalized cDNA pool through the services of Evrogen . Brieflyhttp://main.g2.bx.psu.edu/) [35 Mb of sequence data representing 162,729 reads were generated by 454 sequencing. Quality trimming, adaptor sequence removal and size selection of reads was performed with Galaxy software (su.edu/) . After t-3. Contigs with a BLAST hit to viroid and virus databases were further analyzed by tBLASTx program against 3 legume genomes database and 7 fungi genomes database individually using the same cutoff threshold (see next section “development of a S. sclerotiorum and P. sativum parsing method”).To determine whether any viruses or viroids were present in the fungi-infected plant cDNA sample, viroid and virus databases , includiS. sclerotiorum and pea ESTs from the mixed pool, a procedure based on that proposed by Hsiang et al. in 2003 [S. sclerotiorum (strain 1980) improved the assignment rate. The proxy-fungal genome database was a mixture of Sclerotinia sclerotiorum (strain 1980) and 6 closely related Ascomycete fungi  and a plant genome database including 3 sequenced legume genomes . ESTs that only matched to fungal or plant genome database with an e-value of 1e-03 or better were automatically classified into S. sclerotiorum or pea ESTs, respectively. ESTs, which matched  to both fungi and plant databases, were further analyzed by comparing the e-value of best-hit from fungi and plant genome results. An e-value ratio was determined by dividing the best-hit e-value to fungi and plant genomes from the tBLASTx searches. A cutoff ratio were set at > =1e20 for pea ESTs, <=1e-20 for S. sclerotiorum ESTs and those that fell between 1e-20 and <1e20 were considered to be ambiguous. To acquire a final sort of results, those ESTs without a BLAST hit or those found to be ambiguous were assigned with BLASTn against known S. sclerotiorum or pea ESTs if their identity was above 95% in similarity across 95% of the sequence length. 81,449 pea ESTs  [S. sclerotiorum ESTs  were used to assist in the classification and annotation of contigs.To separate  in 2003  was empledlings)  and 57,7S. sclerotiorum ESTs derived from developing S. sclerotiorum libraries were downloaded from BROAD institute and 18,547 P. sativum ESTs were obtained from the GenBank EST database by search keyword ‘Pisum sativum’. Vector contamination was removed from the downloaded ESTs by BLAST search with UniVec database (GenBank) in P. sativum and S. sclerotiorum ESTs were trimmed. After vector trimming, tBLASTx analysis of the downloaded ESTs was performed separately against the proxy-reference fungal and plant databases  were used as template in PCR with primer pairs for each contig. PCR contained 4 μl of 5 × GoTaq PCR Buffer , 200 μM each dNTP, 2.5 μM each primer, 0.4 U of GoTaq polymerase, and approximately 50 ng of DNA template in a final volume of 20 μl. PCR were held at 94°C for 2 min; followed by 40 cycles of 94°C for 30 s, 60°C for 30 s, and 72°C for 1 min; with a final extension at 72°C for 10 min. PCR products from each contig were separated on a 1% agarose gel and visualized with ethidium bromide.Fifty contigs from  Primer3 . cDNA fr-3 and a high-scoring segment pairs (hsp) filter of 33 were retained so as to assign function to as many contigs as possible while ensuring short matching sequences less than 100 nucleotides were excluded. An annotation configuration with e-value-hit-filter 1.0E-6, annotation cut off “55” and GO weight “10” was selected.The biological function of EST contigs was predicted with gene ontology (GO) terms based on BLASTx analysis using the program BLAST2GO ,59. DefaS. sclerotiorum EST were analyzed using prediction algorithms. Firstly, OrfPredictor [http://www.cbs.dtu.dk/services/SignalP/) with default settings, which predicts the presence and location of signal peptide cleavage sites [The secretory/signal peptides for each redictor  was usedge sites . Both a The authors declare that they have no competing interest.XF performed bioinformatics analysis, validated the EST parsing and drafted the manuscript. KM provided pea lines for analysis and contributed to direction of the study. TC participated in design of the study and conducted signal peptide analysis. TP initiated the project and directed the study. MC directed the project, performed inoculations and initial experiments to develop the normalized cDNA and drafted the manuscript. All authors read, edited and approved the final manuscript.XF is a Research Associate at Michigan State University with a background and interest in expression profiling. KM is an Associate Professor and legume breeder in the Department of Plant Sciences at North Dakota State University. TC is Trait Production Manager at Dow AgroSciences LLC. TP is an Associate Professor of Plant Pathology at Washington State University, with particular interests in the mechanisms of fungal speciation and the genetics of host specificity. MC is an Assistant Professor of Plant Pathology at Michigan State University.Fasta files for 10158 contigs (pea and Sclerotinia ESTs), parsed into ambiguous contigs (1a), no blast-hit contigs (1b), pea contigs (1c) andS. sclerotiorumcontigs (1d).Click here for fileS. sclerotiorumEST contigs encoding potential secretory/signal peptides.Click here for fileComparison of BLASTn and tBLASTx method to assign artificial EST mixture of pea-S. sclerotiorum.Click here for fileThe assignment results of an artificial EST mixture using the tBlastx method against 7 fungal genome databases and theS. sclerotiorumgenome only.Click here for fileComparison of different e-value ratios (fungi/plant) to distinguish species ESTs from the artificial EST mixture.Click here for file


This analysis aims to discuss the implications of the “health asset concept”, introduced by the WHO, and the “investment for health model” requiring a “participatory approach” of cooperative programme development applied on a physical activity programme for socially disadvantaged women and to demonstrate the related costing issues as well as the relevant decision context. The costs of programme implementation amounted to €48,700. Adding the costs for developing the programme design of €48,800 results in total costs of €97,500; adding on top of that the costs of asset assessment running to €35,600 would total €133,100. These four different cost figures match four different types of potentially relevant decisions contexts. Depending on the decision context the total costs, and hence the incremental cost-effectiveness ratio of a health promotion intervention, could differ considerably. Therefore, a detailed cost assessment and the identification of the decision context are of crucial importance. At the moment, more than half of the global population is not physically active to a satisfactory extent . The incThe WHO proclaims the necessity of preventive efforts in policies and the environment aiming at promoting physical activity , 20. AspMoreover, the economic evaluation of those effective primary preventive physical activity programmes suited to a specific group becomes more and more important in a society with scarce resources. It should be based on the identification, measurement, and valuation of the costs and consequences of a prevention programme , 32. TheThe objective of this analysis is three fold. First, we show that the costs of a health promotion programme may comprise more than simply the costs of running the programme. This is particularly true if the approach to developing and implementing appropriate programmes follows the health asset model proposed by the WHO, as this approach calls for resource-consuming activities aimed at identifying and mobilizing the health assets available in the target population and their setting as well as involving the target groups and other stakeholders in the design of the programme. Second, empirical data from a recent participatory research project are presented in order to illustrate that the inclusion of these additional cost elements may alter the results of programme costing and, in consequence, of cost-effectiveness analyses substantially. Third, we want to contribute to the discussion about whether and when the costs of health asset assessment and participatory project development should be included in programme costing to evaluate the cost-effectiveness of the programme under consideration.This paper is based on data from a local neighbourhood project, which was conducted from January 2005 to December 2007. The development and evaluation of the primary preventive interventions was carried out in three different settings: “company,” “sports club,” and “residential district” in the area of Erlangen, Germany. The target population consisted of women “in difficult life situations” partly living in a residential district that was characterized by high rates of unemployment; social welfare recipients and migrants. The key characteristics of being “in a difficult life situation” included the receipt of low income or social welfare payments, low educational attainment, unemployed or in blue-collar occupation, and single parent or member of an ethnic minority. The project aimed to improve the opportunities for physical activity among this service population and define their interests at group meetings. Following the health assets concept and the participatory approach of project development, a setting group and a joint group were set up. The setting group mainly consisted of members of the target population, and the responsibilities within each setting included deciding on actions that should be taken for the promotion of physical activity among them; the joint group consisted of members of the target group, scientific experts, and setting-specific decision makers such as the management of the sports club; the mayor of Erlangen; other stakeholders and representatives of the company, who developed preventive exercise programmes suited to the target population and decided on instruments for evaluation in a cooperative work process. As these prevention programmes should be potentially transferable to other regions, the programmes were implemented and funded according to setting-specific arrangements.The developed intervention programmes consisted of two different kinds of physical activity programmes, a 90-minute programme of moderate-to-high intensity  and a 60-minute programme of low-to-moderate intensity . Both programmes included a mix of different and from session-to-session changing elements of physical activity exercises such as endurance training, workout training, aerobic gymnastics, or relaxation exercises. The programmes took place as indoor programmes in gyms and once a week over a time period of three months, corresponding to a number of totally 11-12 sessions. The programmes were performed as group exercises, with a mean group size of 10–12 women. The exercise classes were directed by certified exercise instructors for grassroots sport and sport for all, being the first grade in the educational hierarchy of sport instructors and trainers and usually practised as a second-job activity. The acquisition of this certificate which is granted be the German public sport associations, is not restricted to an educational background in sport or healthcare; essentially, it requires the successful completion of a course consisting of regularly 120 hours of theoretical and practical training.These two types of physical exercise programmes were offered in all three settings , 30, 35.Totally, 87 women could be recruited for participation in the physical exercise programmes. Recruitment to these programmes was not linked to the obligation to participate in the evaluation research activities of the project. In fact, only 57 women were willing to participate in these research activities. Moreover, recruitment to the programmes as well as to other project activities was done on a self-selection basis. Therefore, women not being in difficult life situations had the option to participate. However, survey results showed that more than 90 percent of the 57 study participants were women in difficult life situations as defined by the project. As the study should produce realistic estimates of the willingness to participate in health promotion activities, no financial incentives were offered to the women for acting as study participants or participating in the physical activity programmes. Quite the contrary, the programmes were offered as programmes liable to charges, even if the level of the fees was fixed somewhat below the customary prices of comparable programmes at the market place.For the evaluation of the programmes, changes in health status and health-relevant behaviour of the women as well as the costs of all phases of the exercise programmes and changes in health care utilisation were measured. Medical and sport scientists estimated the intervention as not invasive for the participants. Medical parameters were examined during the regular consultations of general practitioners by the study participants. Therefore, the study leader did not apply for an approval of the study by the responsible Ethics Committee.However, in this paper, only the costing dimension of this physical activity programme will be analysed and discussed with reference to the “health asset concept” and the “participatory approach” to programme development and according to the cost dimension of the conceptual framework for economic evaluations for physical activity programmes , 36.The project was divided into five phases: (1) assessment; (2) design of the preventive intervention programmes; (3) programme implementation; (4) programme optimisation; (5) dissemination of the preventive programmes.In the first phase—the phase of health asset assessment—options, chances and resources within the three settings were identified according to the health assets concept of the WHO. Therefore, in the first phase, the tasks of the project were to make contact with project partners and decision makers and to conduct face-to-face interviews with women in the target groups (duration of phase 1: six months).In the second phase—the design of the preventive intervention programmes—project partners, representatives of the target group, stakeholders in the related political field and scientific experts took part in establishing setting-specific planning groups as well as an overall joint group. In the setting and joint groups, the programmes were developed in accordance with the participatory approach of the WHO (duration of phase 2: six months).During the third phase, the developed physical activity programmes were implemented and scientifically evaluated (duration of phase 3: twelve months).The fourth phase—optimisation of the programme—aimed at improving the established programmes and initiated the first steps in the rollout of these programmes to other regions of Germany in order to expand these preventive intervention programmes beyond the end of the project (duration of phase 4: six months).During the fifth phase—the phase of dissemination—the conditions for successful project transfer to other regions were to be created (duration of phase 5: six months).In terms of assessing the costs and the cost-effectiveness of the physical activity intervention programme, only the first, second, and third phases are relevant for the health economic evaluation. Note, however, that subject of costing of the third phase of the project was only activities related to the implementation of the health promotion interventions, whereas resource consumption and costs related to the scientific evaluation of the effects of the project were not included in the cost analysis. Also excluded from costing were the last two phases of the project as the main focus of these phases was to publish, promote, and disseminate the programme.As stated above, one purpose of the study was to answer the question of whether the costs of the health assets assessment and the participatory project development should be included in evaluating the programme costs. Therefore, a straightforward implication for the cost analysis is a careful splitting into these project phases of “asset assessment,” “programme design,” and “programme implementation,” thus taking into account the specific requirements of the health asset concept and the participatory approach. The cost measurement of this intervention is based on the development of a detailed cost inventory comprising all relevant cost categories. All these cost categories were assigned to their pertinent costing dimension in a conceptual framework for the economic evaluation of physical activity programmes , 36. In All quantities of resources consumed were assessed retrospectively by questionnaires and personnel telephone interviews for each setting separately. Stakeholders, trainers, members of the target group, and scientists were interviewed to get all utilisation and cost data.All resources were valued using market prices or—if market prices were not available—using values derived from cost manuals in Euros and adjusted to the year 2005. Actual and imputed costs of resource use and (non-) personnel costs were calculated and shown for a physical activity programme lasting for three months.Resources utilized by a productive activity may include fixed assets which by definition are not fully consumed during their short-term use. The resources used in the project under study include two types of these fixed assets: gyms and sport equipment. For both types, two different approaches were applied to calculate their costs. For using the gyms for the physical activity programme, first, the actual rents to be paid by the programme organisers were used; this approach would be appropriate for programme costing from an organiser's or programme payer's view. Second, the imputed rent of a new gym was calculated following the customary capital costs approach; the corresponding cost values would be appropriate for assessing the costs in a societal perspective. The details of calculating the imputed capital costs of the use of gyms are given in Similarly, for the equipment used in the physical activity programmes, cost values based on actual expenses and imputed costs were calculated. The calculation of imputed costs was based on the costs of new equipment, which would be needed according to the recommended manual for these physical activity programmes. Apart from the stereo equipment, all equipment needs are defined as needs per capita of women attending the programmes. These costs were valued with market prices for the year 2005 and amortized over the years of possible usage. The total equipment costs are calculated as costs per person for all types of equipment (except for the stereo system) times the number of participants plus the costs of stereo equipment. Actual equipment expenses were assessed by questionnaire from the programme organisers of each setting from the joint group.Personnel time costs of the scientists, which include, for example, interviews with members of the target group, identification of the assets and contact with decision makers, were valued by typical gross earnings of scientists as public sector employees . Time coFrom a societal perspective, the valuation of the time costs of the participants who take part in physical exercise programmes should be based on the principle of opportunity cost. The valuation of these costs depends on whether the time occupied in physical exercise replaces leisure or labour time (including housekeeping and unpaid activities) and whether the participants regard the exercise itself as a leisure activity. In this study, the time consumed for participating in the programme courses was assumed to be substituted for another type of leisure activity. Hence, the time cost for physical activity was valued at zero costs.A sensitivity analysis was conducted to determine how “sensitively” the results of the cost analysis react to changes in the values of single-cost parameters. Several assumptions were varied, such as the amortisation of equipment, nonpersonnel and personnel costs. The average usage of a single piece of equipment was based on personnel information from a professional sports scientist. Variation in the usage of a single item cannot be excluded; therefore, ±1 year of amortisation of equipment was calculated. Additionally, ±50% of all nonpersonnel cost positions was calculated to reflect the uncertainty of the chosen market prices. Furthermore, the setting and the joint group are made up of different representatives who would incur different personnel time costs according to their work. Thus, ±10% of the average wage rate is added and subtracted to approximate the real average wage rate. The costs of exercise instructors were also calculated from the programme payer's perspective taking the actual wage rate and, for the societal perspective, calculating the additional time of pre- and post-preparation of the physical activity programme according to the questionnaire filled out retrospectively by trainers in the project. The personnel costs of trainers and child care were also calculated within ±10% to account for the uncertainty of the given hourly wage rate.All costs were calculated and presented as minimum (min) costs, maximum (max) costs and personal information (PI) costs. The actual costs from the programme payer's perspective and the societal perspective  are calculated and reported separately.The results of our various cost calculations are shown in detail in different perspectives and partitions in Tables Next, In The total costs the project amounted to 128,353 € if the payers' perspective is chosen, and 133,074 € in a societal perspective. These figures can be subdivided into costs of 35,618 € for the asset assessment, 48,789 € for the programme design , and costs of 43,945 € (payer's perspective) and 48,666 € , respectively, for programme implementation activities. Hence, programme implementation costs accounted only for 34% (payer's perspective) and 37% , respectively, of total project costs. Focussing exclusively on the running costs of the programmes, the corresponding percentages were 3% (payer's perspective) and 6% , respectively. However, one should take into account that the predominant part of programme costs represents variable costs with more or less constant costs per participant so that larger numbers of participants would mean correspondingly higher costs, whereas, the predominant part of residual programme implementation costs and actually all costs accruing in the asset assessment phase and the programme design phase, in contrast, represent fixed costs. Therefore, the proportion of programme costs of total implementation costs and total project costs may well rise with an increasing number of women participating in the physical activity programmes and/or with continuing the programmes in the future.Finally, Dependent on the chosen perspective and the scope of costing, total costs varied substantially. The appropriate scope of costing depends on the type of decision that has to be made. Four typical decisions contexts should be distinguished  perspective, the costs of programme implementation amounted to €43,900 . Adding the costs for developing the programme design of €48,800 results in total costs of €92,700 ; adding on top of that the costs of asset assessment running to €35,600 would total €128,300 . Interestingly, programme implementation costs including recruitment costs make up only 34% to 37% of total costs, dependent on the chosen perspective of analysis.The findings of this study demonstrate that the results of an economic evaluation of a physical activity programme as part of health promotion efforts according to the WHO health asset approach will be highly sensitive to whether or not and to what extent programme development costs are included in the cost calculations. The clarification of this open methodological question is of the utmost importance for the economic evaluation of health promotion activities based on the health asset concept and using a participatory approach to programme development.Therefore, the identification of the decision context that is to be supported by the evaluation as well as the assumptions made in terms of the generalizability of the evaluation results is of crucial importance for the validity of an economic programme evaluation.This study did not answer the question of the cost dimension of an all-encompassing intervention programme. But, finally, this study addresses and invites decision makers to consider these cost dimensions with regard to the willingness-to-pay trade-off and the transferability of the results. Further economic evaluations of effective primary prevention programmes must be performed, and utilisations and costs have to be assessed in detail so that health care decisions may be improved in the future.


Cyp6g1 locus of Drosophila melanogaster, transposable element insertions and a gene duplication event have combined to create at least two adaptive alleles in which the more derived the allele, the greater the insecticide resistance of its bearer Culex mosquitoes have been observed replacing each other within the period of a decade An intriguing observation from some studies of adaptive change is allelic series, where adaptive alleles successively replace each other at a single locus. For instance, at the D. melanogaster. Multiple alleles exist at this locus and they differ in their extent of gene copy number polymorphism and feature a transposable element thought to generate novel transcripts. Thus, this study contributes to an emerging picture that the mutations associated with recent adaptive events may not involve regulatory SNPs or coding SNPs, but complex gene rearrangements Another case of an allelic series is presented in the paper by Magwire et al. Drosophila populations. A survey of insertion site occupancy led Aminetzach and colleagues CHKov1, that has a DOC transposable element inserted into the coding region. This gene is one of a large cluster of 27 paralogs that encode proteins with distant similarity to choline kinases. The pattern of polymorphism around the DOC insertion suggests it was at the center of a very recent and strong selective sweep dating to between 25 and 240 years ago. What selective agent could result in such strong selection on an insect species, so recently? The link to “choline” motivated Aminetzach et al. DOC allele had greater resistance to an OP than a control line with a similar genetic background.The genes featured in the particular rearrangement described by Magwire etal. CHKov genes. The sigma virus has been found to infect up to 20% of D. melanogaster flies in field populations. At least six separate genes that reduce infection rates have been mapped in D. melanogasterref(2)P locus of D. melanogaster have previously been characterized and display patterns of polymorphism consistent with a selective sweep D. melanogaster to molecularly characterize the second of the six genes, ref(3)D. The resistant mutation involves a complex rearrangement of the CHKov1 and CHKov2 genes, with gene duplications derived from the allele originally characterized by Aminetzach et al. DOC insertion allele characterized as resistant to an OP and moderately resistant to sigma viruses, and a derived, highly virus-resistant allele , as determined by its divergence from the ancestral allele, is much older than the use of insecticides and the age of the selective sweep, which was determined from the patterns in nearby polymorphisms. The presence/absence of the DOC insertion is also correlated with the presence/absence of seven amino acid changes affecting a predicted protein that is substantially shortened and altered relative to that encoded by the ancestral allele. Now we know of another selective agent, namely the sigma virus, that is thought to have been infecting D. melanogaster for at least 200 years, but probably longer Drosophila populations in the 1980s, and that is possibly responsible for the recent sweep Magwire et al. CHKov1 and 2, and of the somewhat mysterious group of paralogous proteins currently dubbed “choline kinase–like”. Finally, such examples of allelic series not only tell us about population size and structure, but also provide important empirical examples of how fast adaptive evolution at a single locus can be, and should motivate the search for other “adaptive allelic series” that will help us understand the limits and dynamics of adaptation.Magwire et al.'s


A novel virus, designated Cygnet River virus (CyRV), was isolated in embryonated eggs from Muscovy ducks in South Australia. CyRV morphologically resembles arenaviruses; however, sequencing identified CyRV as an orthomyxovirus. The high mortality rate among ducks co-infected with salmonellae suggests that CyRV may be pathogenic, either alone or in concert with other infections. Cairina moschate). The ducks had been incorrectly fed during a week-long absence of the owner from the farm. The ducks were lethargic and had diarrhea, and the mortality rate among infected ducks was high. Of 150 ducks, 128 died in a 3-day period. Despite treatment with tetracycline, only 5 of the remaining 22 ducks survived.In May 2010, an outbreak of disease at a duck farm at Cygnet River on Kangaroo Island, South Australia, Australia, occurred in 4-month-old Muscovy ducks  was isolated from the ducks and was detected in at least 2 of the following from each animal: feces, spleen, bone marrow, and liver. Histologic lesions were consistent with a disseminated Salmonella infection; thus, a diagnosis of septicemic salmonellosis was made.After disease was discovered among Muscovy ducks on a farm in South Australia, 5 ducks with signs of infection were submitted for investigation to Gribbles Veterinary Pathology ; 2 ducks died during transit. The 3 remaining ducks were euthanized, and postmortem examination showed severe necrotising fibrinous enteritis, multifocal piecemeal hepatitis, and severe fibrinous multifocal splenitis. Pooled samples  from 2 ducks were submitted for disease exclusion at the Australian Animal Health Laboratory, Commonwealth Scientific and Industrial Research Organization . Results of nucleic detection assays excluded Newcastle disease virus and influenza virus as causative agents.Isolation in 9- to 11-day-old embryonated eggs was performed on liver, brain, lung, spleen, and gastrointestinal tissues from 2 ducks after the samples were treated with antimicrobial drugs. In each of 3 passages in the embryonated eggs, embryo death occurred on passage days 4–5 for all tissues except the gastrointestinal tissues. However, when red blood cells from chicks and guinea pigs were used, hemagglutination that would indicate the presence of paramyxoviruses or influenza viruses was not observed in the allantoic fluid. In addition, the agent was filterable, suggesting the presence of a virus.We observed hemolysis on the heads of the embryos and processed the embryos and chorioallantoic membranes for histopathologic studies. Multifocal necrosis was observed in the liver and lung of the embryos and in the chorioallantoic membranes. These necrotic lesions were consistent with an infectious agent. No influenza or Newcastle disease virus antigens were detected in the embryo and chorioallantoic membrane by immunohistochemical testing.We observed cytopathic effects in tissues during additional passages in chicken embryo fibroblasts, Muscovy duck embryo fibroblasts, and Vero and Vero E6 cells. The cytopathic effect observed in Vero cells was minimal in comparison with that observed in other cell lines. We analyzed cultured samples from the allantoic fluid, chicken embryo fibroblasts, and Vero cells by using negative-contrast electron microscopy with nano-W stain . Vero cell monolayers were grown on sapphire disks, lightly fixed, and frozen under high pressure  before being freeze-substituted (4.8/mL), which made initial identification by electron microscopy difficult. Despite minimal cytopathic effect, virus propagation in cell lines was highest in Vero cells , most likely because this cell line lacks interferon. The virus particles had ultrastructural characteristics of arenaviruses and orthomyxoviruses  search. Of the 30 sequences, 3 shared sequence identity with Quaranfil virus, Johnston Atoll virus, and Lake Chad virus, respectively; these viruses are members of the proposed genus Quarjavirus, family Orthomyxoviridae . The implications of this discovery extend to 3 areas.We identified a novel orthomyxovirus virus isolated from Muscovy ducks in South Australia. Examination by electron microscopy showed that the virus has a strong morphologic resemblance to arenaviruses and orthomyxoviruses. Next-generation sequencing enabled identification of the virus as an orthomyxovirus  and to assess the potential role of this virus in disease outbreaks among ducks.Orthomyxoviridae. The family comprises 5 known genera  and 1 tentative genus (Quarjavirus). The proposed genus Quarjavirus contains the 3 virus species: Quaranfil, Johnston Atoll, and Lake Chad viruses (Second, the discovery of this virus provided supportive evidence for the creation of a new genus within the family Third, our findings highlight the value of undertaking a thorough disease investigation. To ensure that all potential causative agents are identified during an investigation, the presence of >1 agent should not be discounted. This notion was elegantly demonstrated a few years ago when Reston Ebola virus was discovered in pigs in the Philippines after an initial diagnosis of porcine reproductive and respiratory syndrome (


Xenotropic-murine-leukemia-virus-related virus (XMRV) was the first gammaretrovirus to be reported in humans. The sequence similarity between XMRV and murine leukemia viruses (MLVs) was consistent with an origin of XMRV from one or more MLVs present as endogenous proviruses in mouse genomes. Here, we review the relationship of the human and mouse virus isolates and discuss the potential complications associated with the detection of MLV-like sequences from clinical samples. Mus germ line less than 1.5 million years ago , as well as in the NIH3T3 cell line, commonly used for many laboratory purposes, including preparation of MLV-based gene therapy vectors [v1 and LNCaP do not express APOBEC3G. Combined with a favorable transcriptional environment [In further support of the idea that XMRV has not infected humans is its high sensitivity to the primate APOBEC3G restriction factor, an interferon-inducible protein, which is constitutively expressed in some  cell types. Indeed, the extensive hypermutation caused by A3G makes it impossible to establish spreading infection of human PBMCs in cell culture  and, whiironment , this prIn an attempt to replicate the findings of XMRV in CFS patients, Lo et al. analyzed plasma and PBMCs from another cohort of CFS patients as compared to samples obtained at a different time and place from normal blood donors . They reXmv proviruses, while the MLV-like sequences of Lo et al. found in CFS and control samples are dispersed among other mouse endogenous proviruses [The possibility of a human gammaretrovirus circulating among the population and potentially having an association with human disease created considerable excitement in the field. A number of researchers proposed that XMRV- and MLV-related sequences represented related findings that strongly supported the conclusion of the association of MLV-like viruses with human disease. However, one should be very cautious about associating the two observations. Xenotropic and polytropic viruses are distinct MLV subclasses, a fact readily observed upon comparing the positions they occupy in phylogenetic trees  Figures and 5. Xoviruses –14  used to obtain and process the assay samples. Unfortunately, such caution is often not the case, particularly in retrospective studies . ClinicaThird, even in the absence of contaminating mouse DNA, a different complication arises from retrovirus-contaminated cell lines used in the laboratory. There are multiple documented cases of such contamination events, which appear to be quite common among laboratories working with retroviruses , 40–43. The overall lesson to be learned here is that extreme measures are required to avoid false associations of mouse viruses with disease, including: (1) rigorous use of highly sensitive assays for detecting mouse DNA contamination of supplies and reagents; (2) frequent testing of cell cultures used in the laboratory for undetected infection with an MLV or another virus; (3) the use of controls that are exactly contemporaneous to the cases and obtained by precisely the same methods using the same materials and reagents. As a few recent papers indicate , 32, 33,