The purpose of this study was to compare pre- and post-surgical healthcare costs in commercially insured total joint arthroplasty (TJA) patients with osteoarthritis (OA) in the United States (U.S.).Using a large healthcare claims database, we identified patients over age 39 with hip or knee OA who underwent unilateral primary TJA (hip or knee) between 1/1/2006 and 9/30/2007. Utilization of healthcare services and costs were aggregated into three periods: 12 months "pre-surgery," 91 days "peri-operative," and 3 to 15 month "follow-up," Mean total pre-surgery costs were compared with follow-up costs using Wilcoxon signed-rank test.p < 0.01). Mean total costs during the follow-up period were 18% higher than during pre-surgery , largely due to an increase in the costs of inpatient care associated with hospital readmissions . Pharmacotherapy costs were similar for both periods ; outpatient care costs were slightly lower in the follow-up period . Mean total costs for the peri-operative period were $36,553.14,912 patients met inclusion criteria for the study. The mean total number of outpatient visits declined from pre-surgery to follow-up (18.0 visits vs 17.1), while the percentage of patients hospitalized increased (from 7.5% to 9.8%) , while mean total healthcare costs increased during the same time period, largely due to increased costs associated with hospital readmissions. Further study is necessary to determine whether healthcare costs decrease in subsequent years. Advanced osteoarthritis (OA) of the hip and knee is associated with severe pain, limitation in function, and impaired quality of life ,2. PatieData were obtained from the PharMetrics Patient-Centric Database, which is comprised of facility, professional-service, and retail  pharmacy claims from over 85 health plans throughout the United States. These plans provide health insurance to approximately 14 million people annually . All patient identifiers in the database are encrypted, and the database is fully compliant with the Health Insurance Portability and Accountability Act of 1996 (HIPAA). As no patient or provider contact was made and patient information was de-identified, Institutional Review Board (IRB) approval was not required.th Revision, Clinical Modification [ICD-9-CM] format), procedures , provider specialty, and charged and paid amounts. Data available for each retail pharmacy claim include the drug dispensed , the dispensing date, and the quantity dispensed and number of days of therapy supplied (selected plans only). All claims include a charged amount; the database also provides paid  amounts.Information available for each facility and professional-service claim includes date and place of service, diagnoses , which represented the most recent period for which complete data were available at the point of study initiation.The source population for this study consisted of all patients with any claims for unilateral primary TKR (CPT-4 code 27447 or ICD-9-CM procedure code 81.54) or unilateral primary THR (CPT-4 code 27130 or ICD-9-CM procedure code 81.51) between January 1, 2006 and September 30, 2007. . Among these patients, the date of the first-noted claim for TKR or THR was designated the "index procedure date", and patients not continuously enrolled in the database for the 12 month period prior to this date ("pre-surgery period") and the 15-month period subsequent to this date ("post-operative period") were excluded from the study sample.a. All pharmacy, professional service, and facility claims were then compiled for all patients in the study sample over the one-year pre-surgery period and the 15-month post-operative period.Patients without diagnoses of OA  in the three-month period preceding surgery were excluded from the study sample, as were those aged less than 40 years as of the time of their index procedure, those enrolled in Medicaid, and persons aged 65 years and older as of the time of their index procedure who were enrolled in a Medicare Advantage plan (because their claims histories are incomplete in the study database). Additional exclusions from the study sample included persons with evidence of any of the following during the one-year pre-surgery period: (1) prior TKR or THR; (2) joint fusion ; (3) procedures suggestive of a prior TKR/THR ; (4) knee or hip fracture  (in 30-day period prior to index procedure date only); (5) other conditions associated with TKR/THR , post-traumatic arthritis , avascular necrosis  benign/malignant bone tumors , or Paget's disease (731.0) during the pre-surgery period, and (6) patients who underwent a second primary TKA or THA during the 15-month period subsequent to the index procedure dateThe demographic and clinical characteristics of study subjects were examined, including prevalence of selected comorbidities, on the basis of information prior to the index procedure date. Patients were assumed to have a particular comorbidity if they had either one or more hospitalizations, or two or more outpatient claims at least 30 days apart, during the pre-surgery period with a corresponding diagnosis code/prescription.Total healthcare costs were aggregated into three distinct periods: pre-surgery period (12-months prior to TJA); "peri-operative" (91-day period including and immediately following TJA); and "follow-up" (12-month period following the peri-operative period). Healthcare costs over each period were subcategorized into (1) pharmacotherapy ; (2) outpatient care , Emergency Department (ED) visits, and diagnostic imaging)]; (3) inpatient care; and (4) all other costs. Pharmacotherapy was further subcategorized as: (1) nonsteroidal anti-inflammatory drugs (NSAIDs), including cyclo-oxygenase (COX)-2 selective NSAIDs; (2) opioids, including tramadol; (3) antidepressants; (4) intra-articular corticosteroid and hyaluronic acid injections; and (5) all other medications.Reimbursed amounts  were used in all analyses of healthcare costs. All costs were expressed on an "as-is" basis . Non-parametric bootstrapping (using sampling [with replacement] from the source population) was used to generate 95% confidence intervals (CIs) for all estimates of healthcare costs . All estMean total pre-surgery costs—for each sub-category and in aggregate—were compared with follow-up costs using Wilcoxon signed-rank tests; the percentages of patients with ≥1 hospitalizations during the pre-surgery versus follow-up periods were compared using McNemar's test. Utilization of healthcare services and costs occurring during the 90-day peri-operative period were excluded from analyses comparing pre-surgery with follow-up so as to compare healthcare costs and healthcare services utilization during the 1-year period prior to TJA with those of the 1-year period following recovery from TJA. A total of 14,912 met the inclusion criteria for the study. The mean age of patients included in the study was 57.3 years, and 57% were women; approximately 17% of patients in our sample were 65 years of age or older (Table p < 0.01]) (Table p = 0.61)., Importantly, the percentage of patients with ≥1 hospitalizations increased .Prescriptions for NSAIDs and opioids declined slightly during the follow-up period relative to the pre-surgery period  (Table p = 0.33).Mean total per-patient healthcare costs during the follow-up period were 18% higher than during the pre-surgery period  and injectable agents , but higher for opioids , antidepressants , and all other medications . On a per-patient basis, outpatient care costs were slightly lower in the follow-up period than in the pre-surgery period , whereas mean per-patient inpatient costs were substantially higher in the follow-up period when compared with the pre-surgery period . All other per-patient healthcare costs were also slightly higher in the follow-up period .However, within pharmacotherapy, mean total per-patient follow-up costs were lower than mean total pre-surgery costs for NSAIDs  ,8. At thWhile previous authors have reported that OA is associated with substantial direct and indirect medical expenditures ,16,17, rOur results indicate that although utilization of healthcare services decreased for most services during the first year following TJA (exclusive of the peri-operative period) in commercially insured patients with OA of the hip or knee, mean total healthcare costs increased, largely due to increased costs associated with inpatient care. Given that the mean length of stay during the peri-operative period  was only 6.9 days, and that 75% of patients spent no more than 8 days in hospital during this time, our findings are most likely associated with readmissions, rather than stays in hospital for the initial TJA of > 91 days. Hospital readmissions following elective surgical procedures such as TJA have become the focus of great debate and concern among healthcare policymakers , and havDespite the interesting findings, our study has several limitations. First, our database consisted of administrative claims for patients enrolled in private insurance plans, who tend on average to be younger than the "typical" cohort who undergoes TJA for OA. Specifically, while patients aged ≥65 years comprise approximately two-thirds of all patients who undergo TJA in the US , they onSecond, our analysis relied upon administrative claims data, which have been shown to have an imperfect correlation with the clinical record . It is pThird, and somewhat related to the second, we did not attempt to adjust for price inflation by expressing costs in terms of a particular "base year". The principal reason that we did not undertake such an adjustment was that we thought it important to examine (and report) actual amounts paid in "real-word" clinical practice during the periods before and after joint replacement. Were we to have expressed all costs in terms of a "base year", such information would not be available. We also note that identification of an appropriate "price index" to adjust healthcare costs is not straightforward. In most instances where this method is employed, a single index  is used to adjust values; implicit in use of this single index, however, is the assumption that all goods and services  experience the same relative change in pricing in a given year. The degree to which that assumption is valid within any given year is unknown. Regardless, to the extent that differences between pretreatment and follow-up costs reflect price inflation, our findings may overestimate differences in healthcare costs between these two periods.Fourth, although recovery from TJA surgery is variable, it is possible that some patients were not fully recovered from surgery by 90 days , and theIn summary, despite slightly lower outpatient care costs and similar costs associated with pharmacotherapy, we found that mean total direct health care costs increased during the 12-month period following recovery from TJA when compared with the 12-month period prior to surgery in commercially insured patients with OA, in large part due to increased costs associated with hospital readmissions. Further study is necessary to determine whether healthcare costs decrease in subsequent years.aPatients who underwent a second primary TKA or THA during the 15-month period subsequent to the index procedure were excluded, as these procedures are often scheduled electively following recovery from the index procedure, they are not indicative or reflective of the condition of the index joint, and they substantially impact the cost and utilization of healthcare services during the time period under study.This study was funded by Pfizer Inc. Alesia Sadosky is a full-time employee of Pfizer Inc. and owns stock in the company. The analyses were conducted by Ariel Berger and Gerry Oster, employees of Policy Analysis, Inc. Policy Analysis, Inc. received financial support from Pfizer, Inc. for the conduct of this analysis and development of this manuscript. Drs. Kevin Bozic and Brett Stacey did not receive any financial support from Pfizer. The funding source did not play a role in the investigation or the interpretation of the results.KB, BS, AB, AS, GO designed the study. AB and AS gathered the data. KB, AB, AS, analyzed the data. KB, BS, AB, AS, GO wrote the initial draft. KB, BS, AB, AS, GO ensured the accuracy of the data and analysis. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6963/12/73/prepub


Pipo was recently described as a new ORF encoded within the genome of the Potyviridae family members . It is embedded within the P3 cistron and is translated in the +2 reading frame relative to the potyviral long ORF as the P3N-PIPO fusion protein. In this work, we first collected pipo nucleotide sequences available for different isolates of 48 Potyvirus species. Second, to determine the biological implications of variation in pipo length, we measured infectivity, viral accumulation, cell-to-cell and systemic movements for two Turnip mosaic virus (TuMV) variants with pipo alleles of different length in three different susceptible host species, and tested for differences between the two variants.P3 cistron did not account for the existence of stop codons in the pipo ORF, but showed that positive selection was significant in the overlapping region for Potato virus Y (PVY) and TuMV. In some cases, variability in length was associated with host species, geographic provenance and/or other strain features. We found significant empirical differences among the phenotypes associated with TuMV pipo alleles, though the magnitude and sign of the effects were host-dependent.In addition to inter-specific variation, there was high variation in the length of the PIPO protein among isolates within species (ranging from 1 to 89 amino acids). Furthermore, selection analyses on the pipo alleles and show that variation in length may be maintained by host-driven selection.The combination of computational molecular evolution analyses and experiments stemming from these analyses provide clues about the selective pressures acting upon the different-length  Potyviridae are one of the largest plant virus families, and many of its members represent major agricultural threats [Potyvirus genus, the largest genus within the Potyviridae, was thought to contain a single functional ORF encoding a polyprotein that is cleaved into 10 mature proteins  by three viral proteases: P1, HC-Pro and NIa-Pro [et al. [pipo (Pretty Interesting Potyviridae ORF). The pipo ORF is embedded within the P3 cistron and is translated in the +2 reading frame relative to the long ORF. Pipo is expressed as a fusion product with the N-terminal portion of P3 protein (ca. 25 kDa), P3N-PIPO, via ribosomal frameshifting or transcriptional slippage at a highly conserved motif at the 5′ end of pipo ORF [et al.[PCaP1 gene in Arabidopsis thaliana results in a severe reduction of TuMV accumulation and in milder symptoms [pipo – in particular protein length – on interactions with host factors and the phenotypic consequences thereof are unknown.The  threats ,2. This  threats -5. Until [et al.  providedpipo ORF . Its lenpipo ORF . Wei et F [et al. and Wen F [et al. have shosymptoms . Very resymptoms . Howeverpipo length was variable among isolates, with most isolates encoding for PIPO polypeptides of 73–76 amino acids long and one isolate encoding for a much shorter polypeptide of only 62 amino acids. These findings motivate the present study, which is organized in two parts. In the first part, we extended the in silico analysis of intra-specific variation in pipo length to the 48 potyvirus species used in the seminal study of Chung et al. [in silico findings using two different length alleles of TuMV pipo. The first allele encodes the wild-type protein of 60 amino acids, hereafter referred to as pipo61. The second allele, dubbed pipo70, has the stop codons at positions 61 and 65 removed by site-directed mutagenesis, while retaining the stop codon at position 70. Thus, this variant encodes a longer protein consisting of 69 amino acids, which occurs in natural virus isolates. Both mutations at positions 61 and 65 were synonymous in the P3 reading frame. Then, we tested for allele-specific differences in infectivity, virus accumulation, and the speed of cell-to-cell and systemic movement in three host species: Nicotiana benthamiana, Brassica rapa and A. thaliana.Recently, during a computational survey of PVY variability , we madeP3 cistron were retrieved from GenBank (48 virus species). Nucleotide sequences were translated and amino acid sequences were aligned with MUSCLE [pipo ORF was located and its size was assigned for each isolate according to the position of the first stop codon in the +2 reading frame. Global information for the procedure is provided in Additional file pipo length, the variables host, geographical origin and strain were retrieved whenever available , PVY and TuMV) using RDP3 version 3.42 [All available coding sequences that included the h MUSCLE  as impleh MUSCLE . Finallyion 3.42  to removion 3.42 -19. RDP3dN– dS, using the fixed-effects likelihood (FEL) and internal branches fixed-effects likelihood (IFEL) [http://www.datamonkey.org[To check the strength of selection at the codon level, we estimated the differences in nonsynonymous and synonymous substitutions rates per site, d (IFEL) ,21. Thesonkey.org.Γ4 + I substitution model in a Bayesian MCMC framework, as implemented in BEAST version 1.7 [8 generations to ensure convergence of all parameters. The inspection of posterior distributions and the estimation of the relevant evolutionary parameters were done with TRACER version 1.5 (tree.bio.ed.ac.uk/software/tracer). The first 10% of sampled trees were discarded as burn-in. Statistical significance of parameters was evaluated using the 95% highest probability density (HPD). In order to estimate the maximum clade credibility (MCC) phylogeny, including its posterior probabilities, the posterior set of trees (showing branch lengths in substitutions) obtained in BEAST was used. To do so, TREEANNOTATOR version 1.6.1 (beast.bio.ed.ac.uk) was used with 10% of the trees discarded as burn-in. The reliability of the MCC tree was evaluated using 95% HPD confidence intervals.Phylogenetic analyses were performed using the GTR + sion 1.7 . Substitpipo length and each of several biological factors while accounting for the underlying phylogeny. BATS version 1.0b2 [PS[AI[MC[4 randomizations were performed to estimate the null distributions of the three statistics.The CONTRAST program from PHYLIP version 3.69 (evolution.genetics.washington.edu/phylip.html), was used to detect correlations between on 1.0b2  was used1.0b2 [PS, the assb2 [PS[AI and the [PS[AI[MC statistipipo alleles were generated by site directed mutagenesis on a plasmid containing TuMV cDNA  and T3141G-PIPO65-2-AS (5′-CTAGAGTGTACGTTTTTCACACATTGCTTGCCCC-3′) to replace stop codons at positions 61 and 65 by the most common codons among all the TuMV isolates, which at the same time only introduced synonymous mutations in the P3 ORF. All constructs were verified by DNA sequencing. DNA extraction was performed with the Qiagen Plasmid Maxi Kit (Qiagen) following the manufacturer’s instructions.TuMV variants harboring different-length lla lily ) tagged N. benthamiana, 19 three-week old A. thaliana and 21 four-week old B. rapa plants were inoculated with DNA . Five μg of DNA (15 μL) and 5 μL of inoculation buffer  were mixed on one leaf per plant and gently rubbed. Inoculated plants were maintained in a growth chamber at cycles of 16 h of light at 25°C followed by 8 h of darkness at 22°C. In addition, control plants were inoculated with buffer and maintained in the same conditions.To compare the accumulation of the TuMV-GFP encoding for different P3N-PIPO proteins, 56 four-week old 2, divided into aliquots and stored at -80°C. RNA extraction from 100 mg tissue per plant was performed using InviTrap® Spin Plant RNA Mini Kit (Invitek) following the manufacturer’s instructions. The concentration of total plant RNA extracts was adjusted to 50 ng/μL for each sample. Quantification of viral load was done by real time quantitative RT-PCR (RT-qPCR), using primers D359 (5′-CAATAGGTGCGAGAGAAGCACAC-3′) and D360 (5′-TAACCCCTGAACGCCCAGTAAG-3′). RT-qPCR reaction mix was prepared using the One-Step SYBR® Prime Script™ RT-PCR Kit II (Takara) with 100 ng RNA per reaction and following the instructions provided by the manufacturer. Amplifications were done using the StepOnePlus™ Sequence Analyzer 7500 (Applied Biosystems) with the following profile: 5 min at 42°C, 10 s at 95°C following 40 cycles of 5 s at 95°C and 34 s at 60°C. RT-qPCR reactions were performed in triplicate for each sample. Quantification results were further examined using SDS 7500 software v.2.2.2 (Applied Biosystems). Standards were prepared by linearization with BglII of the plasmid containing the TuMV infectious clone, followed by in vitro transcription using the mMessage mMachine® SP6 (Ambion) kit and following the manufacturer’s instructions. Known amounts of in vitro transcribed RNA were then added to a healthy plant total RNA preparation.GFP fluorescence was observed with a Leica MZ16F stereomicroscope, using a 0.5× objective lens, and GFP filters (Leica). Infected plants were randomly selected and harvested at different hours post-inoculation (hpi). Plants were ground into fine powder in a mortar with liquid Nm, estimated as the slope of the linear regression of the log-transformed values of virus concentration to time (hpi). For statistical analyses, m values were fitted to a generalized linear model (GLM) with a Gamma distribution and a log-link function; “host” and “pipo” were treated as factorial random factors and “hpi” as a covariable in the model.As a normalized measure of the rate of virus accumulation we used the Malthusian growth parameter, pipo alleles, we followed the protocol described by Lafforgue et al. [N. benthamiana, obtained as described in the previous section, was re-suspended in inoculation buffer and the concentration of viral RNA was made equal for both genotypes. This sap was used to mechanically inoculate 158 four-week old N. benthamiana, 220 three-week old A. thaliana and 109 four-week old B. rapa plants . Inoculated plants were maintained in a growth chamber under conditions of 16 h of light at 25°C and 8 h of darkness at 22°C. Inoculated leaves were removed at 24, 48, 72, 96, 120, and 144 hpi, and plants were maintained for up to two weeks under the same growth conditions. The effect of removing the inoculated leaf at different days post-inoculation (dpi) on the probability of systemic infection was determined by ascertaining whether there was GFP fluorescence in non-inoculated leaves after 9 dpi in the case of N. benthamiana and after 15 dpi for A. thaliana and B. rapa. GFP fluorescence was observed as described above. The frequency of systemically infected plants was fitted to a Binomial logistic regression equation using GLM; “host”, “pipo” and “dpi”  were treated as factorial random factors in the model.To study differences in the speed of colonization of systemic tissues of both TuMV e et al. . In shorN. benthamiana, three-week old A. thaliana and four-week old B. rapa plants were inoculated with ground infected tissue from N. benthamiana as described above. Inoculated leaves were examined at 48, 72 and 96 hpi with a Leica MZ16F stereomicroscope for formation of primary foci of infection. An individual photo was taken for each of many foci per leaf, and zoom was adjusted to the size of the focus and the intensity of fluorescent signal. All photos were normalized introducing the scale of amplification. The area (mm2) of a number of primary infection foci  was calculated using a MATLAB script, using the functions in the Image Processing Toolbox . For statistical analyses, surfaces were divided by π and root-square transformed into effective radii (mm). The transformed data were fitted to a GLM with a Gamma distribution and log-link function; “host” and “pipo” were treated as factorial random factors and “hpi” as covariable in the model.Four-week old Papaya ringspot virus (PRSV)  showed three alternative stop codons, whereas Pea seed-borne mosaic virus (PSbMV), Zucchini yellow mosaic virus (ZYMV), Sugarcane mosaic virus (SCMV), Potato virus A (PVA), and TuMV  only presented two alternative stop codons each , a site within the pipo ORF. A marginally significant positive selection (P = 0.052) was detected by FEL at codon 233 on P3 (amino acid 973 for the polyprotein). This codon is partially coincident with codon 62 from pipo, where a stop codon exists in one isolate (Table P3 according to whether they occur in pipo or in the rest of P3 cistron. An excess of cases of positive selection within pipo was detected (P = 0.044). For TuMV, three positively selected sites were detected with the FEL method at codons 175, 180 and 203 on P3 , all of them occurring in pipo. These three codons partially overlap with codons 11–12, 16–17, and 39–40, respectively, from pipo. An additional selected site outside pipo was also detected with the IFEL method at codon 238 on P3 (amino acid 1061 for the polyprotein). As previously observed for PVY, an excess of cases of positive selection within pipo was detected for TuMV (P = 0.035). In any case, the strength of selection on P3 seems not to account for the presence of alternative stop codons in PPV, PVY and TuMV pipo ORF.Visual inspection allowed us to see that some changes in PIPO length resulted in nonsynonymous changes at the corresponding position of the P3 protein. This observation prompts the question of whether stop mutations were selected for their effects on P3N-PIPO or on P3. To answer this question, we ran selection analyses to evaluate the strength of selection on Next, we sought for an association between the distribution of stop codons and three biological factors: host species, geographic origin and viral strain. In several cases, this association was obvious after visual inspection of the data. For PPV, the distribution of stop codons was related with the three biological factors . However, it is necessary to recall that isolates from a virus do not represent independent observations but are phylogenetically related, thus jeopardizing the results from these simple association tests. Therefore, phylogenetic information has to be taken into account for proper statistical analyses. As before, we focused on PPV, PVY and TuMV data sets, since they encompassed large number of isolates. First, we wanted to test whether phylogenetic structure may explain the association between the distribution of stop codons and the three biological factors. For each virus, independent phylogenetic reconstructions were performed for the analysis of each factor, since the number of isolates for which information was available varied among factor. Phylogenetic analyses with the twelve data sets (four for each virus) were performed as described in the Methods section. After obtaining the MCC phylogenetic tree, BATS [pipo length, along the phylogenies (as described in [pipo (Table Solanaceae family (Table Brassicaceae (80 isolates) or the non-Brassicaceae (11 isolates). In this case, a significant association was observed, although it only arose because of the non-random distribution across the phylogeny of isolates from the Brassicaceae group .All these associations were statistically significant . For PPpo Table . To the ly Table , and thuP > 0.33 in all cases).Next we used Felsenstein’s independent contrasts method  to evalupipo, suggesting that the apparent association between both traits may merely result from the phylogenetic relationships between isolates. To experimentally test whether pipo length had an effect on virus infection in different host species, we evaluated four different fitness components for both TuMV strains carrying the two pipo alleles of different lengths found for this virus  and the Brassicaceae .As discussed in the previous section, Tables us Table , pipo61The first fitness component analyzed was infectivity, that is, the probability of establishing an infection upon inoculation of a given viral dose ,33. Consχ2 = 70.8398, 2 d.f., P < 0.001), with growth rates being larger in A. thaliana and N. benthamiana and lower in B. rapa. More interestingly, a highly significant host-species-dependent effect of the pipo allele was found . TuMV-pipo61 grew 7.8% faster in N. benthamiana and 3.6% faster in A. thaliana than the virus carrying the longer pipo70 allele. In contrast, the virus carrying the pipo70 allele grew 10.9% faster in B. rapa.The second fitness component evaluated was Malthusian growth rate, which is a proxy for the rate of virus accumulation per day Figure A. Signifpipo alleles on the rate of foci expansion was detected . However, significant differences among slopes exist in the case of N. benthamiana plants , with TuMV-pipo61 having a 2.55 (ratio of slopes) times faster cell-to-cell expansion than the virus carrying the long allele. No significant effects were observed in the other two hosts.Next, we tested for differences between alleles in the rate of cell-to-cell movement by quantifying the average effective radius of expanding foci at increasing hpi, and comparing these dynamics across hosts Figure B. Overalet al. [pipo allele was found , although there was a significant three-way interaction . This interaction demonstrates that the time required for triggering a systemic infection indeed depends on the interaction between the host species and the pipo allele. At one extreme, systemic infection occurs sooner in N. benthamiana than in the other two hosts, and it is faster for the pipo70 allele  [P3 and pipo ORFs, although it has been shown that these effects on virulence are due to the amino acid change in P3 but not in P3N-PIPO [P3 cistron of TuMV that is essential for adaptation to Raphanus sativus also changes an amino acid in the P3N-PIPO protein [pipo is expressed as a fusion product with the N-terminal portion of P3 does not preclude from the potential influence of P3N-PIPO on virulence determinants mapped onto P3 and upstream P3N-PIPO. Since P3N-PIPO can also be involved in other functions [The fact that tch virus, TuMV [3tch virus-37, PSbMtch virus, ZYMV [3tch virus,40, and us (SMV) . HoweverP3N-PIPO . Also, a protein , but theunctions , these ppipo size is a common feature in potyviruses. In this sense, five out of the eight viruses showing more than 10 isolates presented alternative stop codons, whereas this feature was only observed for three out of the 40 viruses for which less than 10 isolates were available. To date, experiments with the pipo ORF have consisted of introducing nonsynonymous mutations [Our results suggest that intra-specific variability in utations  or drastutations ,9. Howevpipo stop codons. We have not observed differences in infectivity, whereas we did observe differences in spread and accumulation. These observations suggest that the length of different alleles has no effect on initiating the infection. On the other hand, pipo length does have quantitative effects on virus spread, as might be expected for a mutation affecting the viral movement protein. Moreover, these effects are host dependent, thus further enhancing their potential selective value: certain alleles may be fitter in some hosts while other alleles may be so in alternative hosts.Our experimental results confirm variability of the adaptive value of different pipo length is common. Our results also indicate that this variation may be maintained by host-driven selection, although further studies using other potyvirus models will be needed to shed some light on the generality of the results here shown.Available information for the different poytivirus species suggests that intra-specific variability in The authors declared that they have no competing interests.JH and JMC performed the computational analyses, JH performed the experiments, SFE analyzed the empirical data, JMC and SFE conceived the study, JMC and SFE drafted the manuscript. All authors have read and approved the final manuscript.Table S2. Available information for isolates belonging to Plum pox virus. The last three columns indicate the presence (+) or absence (-) of the alternative stop codons in each isolate. Table S3. Available information for isolates belonging to Potato virus Y. The last seven columns indicate the presence (+) or absence (-) of the alternative stop codons in each isolate. Table S4. Available information for isolates belonging to Turnip mosaic virus. The last two columns indicate the presence (+) or absence (-) of the alternative stop codons in each isolate. Table S5. Available information for isolates belonging to Sugarcane mosaic virus. The last two columns indicate the presence (+) or absence (-) of the alternative stop codons in each isolate. Table S6. Available information for isolates belonging to Pea seed-borne mosaic virus. The last two columns indicate the presence (+) or absence (-) of the alternative stop codons in each isolate. Table S7. Available information for isolates belonging to Papaya ringspot virus. The last three columns indicate the presence (+) or absence (-) of the alternative stop codons in each isolate. Table S8. Available information for isolates belonging to Zucchini yellow mosaic virus. Strain is not available for any of the isolates. The last two columns indicate the presence (+) or absence (-) of the alternative stop codons in each isolate. Table S9. Available information for isolates belonging to Potato virus A. The last two columns indicate the presence (+) or absence (-) of the alternative stop codons in each isolate.Potyviruses analyzed in the present study. For each virus, the GenBank accession number of the reference sequence and its estimated PIPO size is given. The last two columns indicate the number of available isolates for each virus and the observed alternative stop codons, if present. The number of isolates showing a given stop codon is indicated in parentheses. Click here for file


A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km. Highly Pathogenic Avian Influenza virus (HPAI), Classical Swine Fever Virus (CSFV), and Foot-and-Mouth Disease Virus (FMDV) are highly contagious viruses affecting livestock and are among the World Organisation for Animal Health (OIE) listed diseases. The consequences of their recent epidemics in the Netherlands The mechanisms underlying the between-farm spread of HPAI are not clearly understood, especially those of indirect transmission (involving vectors or fomites and possibly wind-borne transfer), as opposed to direct transmission  With stringent control measures put in place during epidemics including bans on the movement of animals, the direct spread of the virus is reduced. Therefore, indirect routes such as contamination of personnel and fomites do become the only pathway of virus spread. Indirect transmission could arise from human vectors transferring infective excreta such as manure from infected to recipient animals The need to determine whether wind-borne transportation of the virus is one of the untraced routes of HPAI spread between farms is apparent. The simplest way possible is that where the virus is transported by wind from an infected farm directly to an uninfected farm as has been considered in plume models for FMDV spread Davis et al. We do this by developing a model for wind-borne transmission of HPAI between farms, and comparing its predictions for the distance-dependent wind-borne transmission risk with the observed transmission risk in the Dutch 2003 H7N7 epidemic In this section, we describe all the processes involved in the wind-borne spread of disease between two poultry farms. We start by modelling particle dispersion and deposition and proceed to determine the quantity of viable virus available in the deposited quantity. We then determine the distance-dependent risk of infection for farms downwind of an infected farm. Lastly, we compare our model estimates for distance-dependent probability of infection with a kernel derived from the Dutch 2003 HPAI epidemic data Dust plume dispersion is assumed to originate from an elevated point source on a poultry house. A model of the motion and deposition of the (contaminated) dust plume is then used to calculate the quantity of viable virus in dust deposited at various locations as the plume moves. This model incorporates particle settling and pathogen decay and the principles of a 3D-Gaussian Plume Model (GPM) and assumes no barriers to the plume. This is a worst-case assumption for the Dutch situation since these barriers would reduce the distance covered by wind-dispersed particles.v, into the classic GPM (Supporting Information S1). Particle settling leads to a shift, of magnitude H is the effective release height, u is the wind speed, t, x away from the source and The GPM used in this study was obtained by solving a simplified version of the general Advection-Diffusion (A–D) equation (Supporting Information S1). The classic GPM does not consider that during downwind motion the dust particles may settle down due to gravitational and other forces. However, we consider this process to be essential for two reasons: first, particle settling reduces the amount of dust moving further downwind, and second, we will be interested in the exposure of animals downwind to virus in settled dust. Hence, the first extension we make is incorporating particle settling, at a velocity x, z from negative infinity up to zero and multiplying it with the lateral dispersion component asx from the source Particle deposition occurs as a consequence of the vertical plume expansion due to diffusion and particle settling due to gravitation. To model deposition, we first calculate the cumulative quantity deposited per square meter between the source and distance 2a units wide (crosswind direction) and 2b units long (downwind direction). If this area is always directly under the plume centre , we obtain this quantity by first integrating equation (3) with respect to y between the limits x between the limits r from the source farm and at an angle x is between the limits y is between the limits 4ab square units, located at a distance r from the source asWe then calculate the total quantity deposited per second on a rectangular area t. It takes into account virus decay during plume flight and while on the ground after deposition and its distance-independence is due to the fact that decay starts as soon as particles are released.Consider virus particles emitted in a “puff” spanning a time interval t is obtained by taking the product of equations (4) and (5) asThe total contaminated quantity r, which again gives a complicated expression. Hence a numerical exploration of the effects of varying the model parameters is performed in the sensitivity analysis (Supporting Information S1).One question of interest is the distance from the source to the point of maximum deposition. This distance is calculated by solving the equation 10EID50. Subsequently, we determine the probability of infection of a chicken for a given virus amount inhaled based on a dose-response curve that we obtain by fitting to experimental data of Spekreijse et al. To translate the predicted deposition of dust into virus amount we use results reported by Shortridge et al. −1. Furthermore, since the components of farm dust which include faeces, skin and feathers, bedding material and feed-remains are not equally infectious, part of this material acts merely as a vector onto which the infectious part colloids during dispersal. The contaminated fraction c describing how much the average concentration is exceeded closely above the ground. We use the average of the ratios of dust concentrations at 40 cm and 260 cm from Chicken activities such as pecking, wing flapping, dust bathing and other movements suspend the already settled virus particles that they subsequently inhale. A study on determining the lung volume of chickens N birds, the hourly probability k birds is given byUpon intake of the virus, infection may or may not occur depending on the virus amount inhaled. Given a successful first infection, subsequent infections at the farm level may occur, resulting into a major outbreak on the farm. In this study, infection risk is defined as the ability of the deposited virus to cause an infection of at least one susceptible bird in a flock and this bird being able to set off a major within-flock epidemic. For a flock with k initial infections is k initial infections and the probability that these infections cause a major within-flock epidemic asFor a disease which has a within-flock basic reproduction ratio The contribution of the wind-borne route to the epidemic is here determined by the fraction of new cases that it can explain. We use the concept of the between-farm (basic) reproduction ratio (as defined in the Supporting Information S1) to compute this fraction.General and HPAI-specific parameter estimates are used in this study to quantitatively assess the possible role of the wind-borne route in the indirect transmission of the virus. They are categorised into dispersion, pathogen, host and farm related parameters.Dispersion-related parameters include the emission quantity th and May 31st 2003) (available on the website: http://www.knmi.nl/klimatologie/daggegevens/selectie.cgi). From the downloaded data, we calculated the average (minimum-maximum) wind speed during the outbreak as The pathogen-specific parameters are the decay rate constant The model predictions presented here were obtained using the parameters given in nd speed , settlinnd speed , eddy dind speed , effectind speed , and decnd speed . In FiguFollowing wind-borne dispersal of contaminated farm dust, we calculated the quantity of contaminated dust present on a given space , we analysed the effects of varying wind speed , settlinSince we were interested in assessing the role of wind-borne spread during the Dutch 2003 epidemic that involved an H7N7 HPAI subtype, we chose a within-flock basic reproduction ratio We conclude that the wind-borne route cannot fully explain observed patterns of between-farm spread of the virus especially for longer distances. This conclusion is robust to changes in uncertain model parameters. We also estimate that, up until 25 km distance, wind-borne transmission could explain up to 24% of the observed infections. This latter percentage is subject to some uncertainty. Nevertheless, this result supports the need to identify supplementary mechanisms that aid the transportation of the virus between locations. It also implies that: a) the experienced neighbourhood transmission was not entirely due to wind dispersal of the virus, b) virus transportation may either have entirely been by a different mechanism in a single-stage process, or c) virus transportation may have been by a multi-stage process that also involves the wind dispersal. Consequently, in-depth studies on the role of fomites in the transfer of infectious material between flocks are essential to develop alternative models for indirect transmission.The deposition modelling approach developed here is likely to be relevant to modelling of wind-borne spread of other livestock diseases as well. Particles to which pathogens may be attached in wind-borne dispersal, have a size range of 1 to 100 µm and they sediment under gravity Figure S1Effect of varying wind speed u on the contaminated dust quantity present on a 4 m square space at various distances from the source at the moment that the deposition arising from a 24 hour-long emission period ends.(TIF)Click here for additional data file.Figure S2Effect of varying the settling velocity v on the contaminated dust quantity present on a 4 m square space at various distances from the source at the moment that the deposition arising from a 24 hour-long emission period ends.(TIF)Click here for additional data file.Figure S3The effect of varying the vertical eddy diffusivity zK on the contaminated dust quantity present on a 4 m square space at various distances from the source at the moment that the deposition arising from a 24 hour-long emission period ends.(TIF)Click here for additional data file.Figure S4Effect of varying the effective release height H on the contaminated dust quantity present on a 4 m square space at various distances from the source at the moment that the deposition arising from a 24 hour-long emission period ends.(TIF)Click here for additional data file.Figure S5Effect of varying the decay rate  on the contaminated dust quantity present on a 4 m square space at various distances from the source at the moment that the deposition arising from a 24 hour-long emission period ends.(TIF)Click here for additional data file.Figure S6Comparison of the distance-dependent probability of infection as estimated by Boender et al. (2007) from the 2003 epidemic data and our wind-borne spread model prediction with default parameter values and: Panel A. The virus survival was increased from 4 to 7 days); Panel B. The particle settling velocity was reduced from 0.01 m/s to 0.005 m/s); Panel C. The within-flock basic reproduction ratio was increased from 22.7 to 100.(TIF)Click here for additional data file.


Gammaretroviruses of several different host range subgroups have been isolated from laboratory mice. The ecotropic viruses infect mouse cells and rely on the host CAT-1 receptor. The xenotropic/polytropic viruses, and the related human-derived XMRV, can infect cells of other mammalian species and use the XPR1 receptor for entry. The coevolution of these viruses and their receptors in infected mouse populations provides a good example of how genetic conflicts can drive diversifying selection. Genetic and epigenetic variations in the virus envelope glycoproteins can result in altered host range and pathogenicity, and changes in the virus binding sites of the receptors are responsible for host restrictions that reduce virus entry or block it altogether. These battleground regions are marked by mutational changes that have produced 2 functionally distinct variants of the CAT-1 receptor and 5 variants of the XPR1 receptor in mice, as well as a diverse set of infectious viruses, and several endogenous retroviruses coopted by the host to interfere with entry. The various inbred strains of laboratory mice and wild mouse species differ in their susceptibility to mouse gammaretrovirus infection and to virus-induced diseases. Host resistance is due to numerous constitutively expressed antiviral factors that target specific stages of the retroviral life cycle. These host restriction factors can block entry, postentry uncoating and reverse transcription, trafficking, integration, assembly, and release . The firInfectious mouse leukemia viruses (MLVs) of three subgroups have been isolated from laboratory mice, and these subgroups were initially defined by their species tropisms. The ecotropic MLVs (E-MLVs) infect only mouse or rat cells and use the amino acid transporter CAT-1 as receptor. The xenotropic MLVs (X-MLVs) infect cells of non-rodent species , and pol Receptor choice is determined by the N-terminal portion of the MLV Env, the receptor-binding domain (RBD) –11. The Slc7a1) encodes a glycoprotein with 14 putative transmembrane domains, and it functions as a cationic amino acid transporter . Th. ThM. dun FrMLV) . Mus, and CAT-1 receptor variants have been described in hamsters and rats . The only known functional variant of this receptor in mice is dCAT-1 of M. dunni, and it is not clear if this variant arose in mice exposed to virus; the single available M. dunni sample is a cell line that does not carry E-MLV ERVs indicative of past infections , 94Xpr1 p Xpr1 mutants that have substitutions in ECL3 but identical ECL4 sequences. These same viruses also differ in their infectivity for cells with mXpr1, c,Xpr1 and sxvXpr1, which have identical ECL3 sequences but different deletions in ECL4. The involvement of residues in multiple receptor domains is also characteristic of other retrovirus receptors . Tng trade , 82, 131ng trade –134. The XP-MLVs are capable of infecting cells of other species, including humans . Cells oMice are important vectors of diseases that infect humans and their livestock , and MLVMus XPR1, K500 and T582 [Xpr1 in these cells resulted in susceptibility to X-MLV but not XMRV, and analysis of interspecies somatic cell hybrids suggested that BHK cells lack a secondary factor needed for XMRV infection [It is clear that XMRV differs from MLVs isolated from mice in several biological properties, including host range and receptor usage. The two critical residues for X-MLV entry in and T582 , indepenand T582  or for tand T582 . While Tand T582 , 17. XMRnfection . These rRetrovirus entry is dependent on the presence and accessibility of specific cell surface receptors. Mutational changes in these receptors and in the receptor attachment sites in the virus Env can alter the very first step in the virus life cycle and can thus have profound consequences for virus replication. Inhibition of virus entry has been a particularly effective antiviral tactic in mice infected with MLVs as well as with other gammaretroviruses . Entry ienv genes to interfere with virus infection. There is also evidence of additional host factors or co-factors that influence entry of the mouse gammaretroviruses, some of which are affected by glycosylation [For the laboratory mouse MLVs, alterations in host receptors and/or virus Env can result in virus restriction, can alter the type and tempo of infection-induced pathology, and may also influence postentry events . The intsylation , 154. Fu


In 2010, a chimpanzee died at Copenhagen Zoo following an outbreak of respiratory disease among chimpanzees in the zoo. Identification of coxsackie B3 virus, a common human pathogen, as the causative agent, and its severe manifestation, raise questions about pathogenicity and transmissibility among humans and other primates. Picornaviridae, genus Enterovirus) are recognized: CB1–6. CBV infections are common in humans and usually cause minor symptoms. However, CBVs are also linked to several serious acute manifestations in infants, children, and adults. CBVs are one of the most common causes of meningitis and can also cause encephalitis  (family Pan troglodytes) and bonobo (P. paniscus) are the closest living relatives to humans  that had been born at the zoo; typical lifespan for such chimpanzees is 50-60 years. Following 36 hours with respiratory symptoms, lethargy, and decreased appetite, the chimpanzee died on October 25.Chimpanzees at the Copenhagen Zoo  zoo are housed together and allowed contact with each other at all times. In October 2010, respiratory symptoms  developed in all chimpanzees at the zoo; however, a 7-year-old female chimpanzee was particularly affected. She was a West African chimpanzee . Reactions were performed in 25μL volumes comprised of 1× HiFi buffer, 2 mmol/L MgSO4, 0.2 mmol/L dNTPs, 0.4 μmol/L each primer, 1 μL template cDNA, and 1 U enzyme. Cycling conditions were 94°C for 2 min; 35 cycles of 94°C for 30 s, 55°C for 30 s, and 68°C for 7 min 45 s; followed by a final extension at 72°C for 7 min.We further characterized the virus by using RNA extracted from the heart. Virus was reverse-transcribed by using SuperScript III First-Strand Synthesis System for RT-PCR , and then subjected to PCR amplification by using an enterovirus-specific, long-range PCR approach. A near complete viral genome  was amplified with primer sequences 5′-GGTGCGAAGAGTCTATTGAGC-3′ and 5′-CACCGAAYGCGGAKAATTTACCCC-3′. PCR amplification was performed by using the Platinum www.ncbi.nlm.nih.gov/genomes/GenomesHome.cgi?taxid=10239), was constructed, against which all sequence reads were compared by using BLASTn (http://blast.ncbi.nlm.nih.gov/Blast.cgi). This comparison revealed 89,121 sequence reads with similarity to CB3 virus sequences . Using a complete genome of a CB3 virus  as reference, we mapped all sequence reads with similarity to enteroviruses by using SMALT software . A consensus sequence constituting the reported CB3 virus was constructed from the mapped reads (GenBank accession no. JN979570). To assess the likelihood of the reported CB3 virus being of human origin, we performed phylogenetic analysis by using a neighbor-joining method. The phylogeny was generated by using published full-genome CBV sequences; all CBV serotypes and the chimpanzee CB3 virus were represented . A local database containing all virus sequences, except those for HIV, retrieved from the Viral Genomes database in GenBank  was generated (data not shown). Overall, the plot showed >95% similarity between the 2 sequences; however, 83% similarity was shown in the 2A region of the sequences. Such a change in the 2A protein could theoretically contribute to altered pathogenicity of the CB3 virus, although whether this is the case would require additional analyses.A CB3 virus was detected at extremely high concentration in the heart muscle of a chimpanzee that died from myocarditis. Given the close similarity of the near-complete viral genome sequence to that of human CB3 viruses, the source of the virus was likely a human. Infection of the chimpanzee colony most likely occurred through close contact with an animal keeper or other zoo employee. Alternate explanations, such as transmission by contact between the chimpanzee colony and other zoo animals or zoo visitors, are unlikely because the chimpanzees had no contact with other animals, and they are separated from the public by a 4-m-high glass wall.Enterovirus genus, some enteroviruses that infect humans also infect animals , and some primates can be infected with several other enterovirus types. CB5 virus was isolated from an infant chimpanzee with a fatal illness (–Within the This report shows that transmission of viruses from humans to chimpanzees is possible and can be fatal. Whether enteroviruses are regularly transmitted between humans, chimpanzees, and other primates, and whether some primates serve as reservoirs for mutation of enteroviruses that can then infect other primates remains to be investigated.


As obligatory intracellular pathogens, viruses exploit various cellular molecules and structures, such as cellular membranes, for their propagation. Enveloped viruses acquire lipid membranes as their outer coat through interactions with cellular membranes during morphogenesis within, and egress from, infected cells. In contrast, non-enveloped viruses typically exit cells by cell lysis, and lipid membranes are not part of the released virions. However, non-enveloped viruses also interact with lipid membranes at least during entry into target cells. Therefore, lipids, as part of cellular membranes, inevitably play some roles in life cycle of viruses.Role of Lipids in Virus Replication”, brings together reviews by experts of both enveloped and non-enveloped viruses. They discuss the latest views on interactions of viruses with lipids and/or lipid-based structures in various aspects of the virus life cycle, ranging from entry, to genome replication, to assembly and release.Studies of lipids in the virus life cycle, first as components of enveloped viruses, trace back to several decades ago. Since then, however, our understanding of the roles of lipids in cellular functions has evolved dramatically; lipids are no longer thought to be just plain building blocks of membrane bilayers. Some lipids promote molecule compartmentalization through active participation in formation of microdomains/vehicles, whereas others bind specific proteins thereby serving as signaling molecules. With the emergence and establishment of concepts such as lipid rafts and headgroup-specific lipid-protein interactions ,2, our uTaube, Jiang, and Wobus [All viruses need to attach to the host cell surface and gain access to the cytoplasm where they replicate. Glycosphingolipids, with diverse sugar chain modifications, serve as virus receptors for a wide variety of viruses. nd Wobus  describeKielian, Chanel-Vos, and Liao [and Liao  take us per se have begun to emerge only recently. Stapleford and Miller [Positive-sense RNA viruses reorganize cellular membranes to form membranous structures with which genome replication complexes associate. However, specific roles played by lipid molecules d Miller  discuss Targett-Adams, Boulant, Douglas, and McLauchlan [One of the most clinically relevant positive-sense RNA viruses is hepatitis C virus (HCV). For this virus, the connections between lipid metabolism and RNA genome replication, infectious particle assembly, and entry, are becoming increasingly clear. Lauchlan  review tBhattacharya and Roy [Recent data suggest that in some cases non-enveloped viruses exit without lysis of producer cells.  and Roy  discuss Laliberte and Moss [Poxviruses acquire multiple lipid membranes during their replication and assembly in the cytoplasm. Recent studies suggest the importance of anionic phospholipids present in viral membranes for efficient virus entry. and Moss  describeWaheed and Freed [nd Freed  describeAs summarized above, this special issue provides the latest view of lipid-virus interactions during entry, genome replication, morphogenesis, and exit, for a wide variety of viruses. The theme emerging from the reviews in this issue is that lipids play active roles in the virus life cycle as host cofactors rather than inert constituents of cell membranes. Since the processes lipids facilitate are essential for virus propagation, advances in our understanding in this field also promise new insights into prospects for developing new therapeutic strategies.


In addition, we previously demonstrated exogenously added GM3 can competitively inhibit porcine rotavirus binding and infectivity of host cells in vitro. Sialyllactose, the carbohydrate moiety of GM3, is approximately 3 orders of magnitude less effective than GM3 at inhibiting rotavirus binding to cells. Furthermore, production of therapeutic quantities of GM3 ganglioside for use as an oral carbomimetic in swine is cost prohibitive. In an effort to circumvent these problems, a sialyllactose-containing neoglycolipid was synthesized and evaluated for its ability to inhibit rotavirus binding and infectivity of host cells. Sialyllactose was coupled to dipalmitoylphosphatidylethanolamine (PE) by reductive amination and the product (SLPE) purified by HPLC. Characterization of the product showed a single primulin (lipid) and resorcinol  positive band by thin layer chromatography and quantification of phosphate and sialic acid yielded a 1:1 molar ratio. Mass spectroscopy confirmed a molecular weight coinciding with SLPE. Concentration-dependent binding of rotavirus to SLPE was demonstrated using a thin-layer overlay assay. Using concentrations comparable to GM3, SLPE was also shown to inhibit rotavirus binding to host cells by 80%. Furthermore, SLPE was shown to decrease rotavirus infection of host cells by over 90%. Finally, preliminary results of in vivo animal challenge studies using newborn piglets in their natural environment, demonstrated SLPE afforded complete protection from rotavirus disease. The efficacy of SLPE in inhibiting rotavirus binding and infection in vitro and in vivo, coupled with its relatively low-cost, large-scale production capabilities make SLPE a promising candidate for further exploration as a possible prophylactic or therapeutic nutriceutical for combating rotavirus disease in animals. Most importantly, the results presented here provide proof of concept that the nutriceutical approach of providing natural or synthetic dietary receptor mimetics for protection against gastrointestinal virus infectious disease in all species is plausible.Group A rotaviruses are a major cause of diarrhea in the young of many mammalian species. In rotavirus infected piglets mortality can be as high as 60%. Previous research in this laboratory has identified a porcine intestinal GM Rotaviruses are a major cause of diarrhea in the young of most mammalian species and the most important cause of severe dehydrating diarrhea in children worldwide. In excess of 60,000 deaths caused by rotavirus occur in infants and young children annually . NeonataMost herds are infected with porcine rotavirus, especially Group A strains, and there is a disease-producing synergism with intercurrent infection with other enteropathogens. Rotaviruses display a tropism for the villous enterocytes lining the small intestine. Productive infection results in cell lysis. Although some minor variations in the pathophysiological responses exist among species, the most prominent and consistent lesion is villous atrophy. in vitro and in vivo between human and animal rotavirus [Two oral human rotavirus (HRV) vaccines were recently licensed: a three-dose human-bovine reassortant multivalent rotavirus vaccine, RotaTeqTM in the US, Canada and ~30 other countries; and a two-dose attenuated HRV (AttHRV) monovalent vaccine (G1P1A8)), RotarixTM in more than 90 countries, including countries of the European Union, Latin America, Asia and Africa (for review see ). Both votavirus ,7. With ), Rotariotavirus . In contotavirus ,12,13,14Despite remarkable progress in rotavirus vaccine development for both animals ,15,16,17in vitro experiments, Group A porcine rotavirus (OSU strain (P9(7)G5)) was propagated in MA104 cells (ATCC HTB 37) and triple and double-layered virus particles isolated by gradient purification using the following modification of standard techniques [in vivo studies, the above virus was passed in newborn piglets and partially purified from feces as previously described [For all chniques ,24,25. Aescribed . 3:MeOH (2:1) under constant stirring in a round bottomed flask. The tube containing the SL was rinsed with methanol (5 mL) and added to the flask, and the reaction mixture was incubated at 60 °C for two hours. At the end of this incubation, 1 mL of reducing agent NaCNBH4, (10 mg) dissolved CHCl3:MeOH:acetic acid  was prepared fresh and added to the reaction mixture. Four more 1 mL aliquots of reducing agent were added to the reaction at approximately 4 h intervals and appearance of reaction products monitored using analytical thin layer chromatography (TLC) and orcinol, resorcinol, and primulin sprays to identify bands containing neutral carbohydrate, sialic acid, and lipid, respectively. Following approximately 22 h total reaction time, the mixture was dried by rotary evaporation, dissolved in 20 mL water, and dialyzed against 5 L of H2O for 5 h. The dialysis was repeated twice, the sample lyophilized, and the SLPE (or LPE) resuspended in 25 mL CHCl3:MeOH:H2O  and purified using preparative HPLC (below). Sialyllactose or lactose was linked to dipalmitoylphosphatidylethanolamine (PE) to yield sialyllactosylphosphatidylethanolamine (SLPE) or lactosylphosphatidylethanolamine (LPE) via reductive amination using modifications of a previously described procedure . Briefly3:MeOH:H2O  at a flow rate of 2 mL/min and eluted using the following sequence: 0–30 min, 100% CHCl3:MeOH:H2O ; 30–75 min, a linear gradient of CHCl3:MeOH:H2O from  to (55:45:10); 75–120 min, 100% CHCl3:MeOH:H2O (55:45:10); 120–125 min, a linear gradient of CHCl3:MeOH:H2O from (55:45:10) to (30:60:20); and from 125 to 160 min, 100% CHCl3:MeOH:H2O (30:60:20). Fractions were collected every 2 min and continuously monitored by stream splitting and refractive index measurements using an evaporative laser light scattering detector . Detector settings were as follows: drift tube temperature = 60 °C, exhaust temperature = 35.9 °C, gas (N2) flow rate = 0.7–0.9 SLPM and pressure = 6.8 psig; the solvent pressure was 0.2 psig. Purity of the HPLC fractions and final SLPE or LPE pool was assessed by analytical TLC [Aliquots (5 mL) of SLPE or LPE were filtered 0.45 µm nylon filters and applied to 10 µm silica preparative HPLC column . The sample was applied to the column in CHClical TLC ,24,25. For characterization of the purified SLPE or LPE reaction product, molecular mass and phosphate to sialic acid molar ratios were determined using the following assays. Sialic acid was determined by modification of an HPLC/thiobarbituric acid method . Brieflyversus water and then lyophilized. The average number of sialyllactose residues coupled to BSA was 37 and was determined following acid hydrolysis by HPAEC-PAD monosaccharide analysis [Sialyllactose was coupled to BSA via reductive amination as previously described . The Reaanalysis  and protanalysis . 3:MeOH:H2O at a final ratio of 1:1:1.1 (v/v), the organic layers pooled and evaporated to dryness. Reaction products were characterized using analytical TLC [Acetic anhydride was added in five portions to samples containing PE, LPE, and SLPE in a 1:1 chloroform:methanol solution containing sodium bicarbonate as previously described . Tubes wical TLC ,25. 125I was performed as previously described [2 as previously described [2, pH 7.5) were sonicated as described. The sample was made 1 M in CaCl2 by addition of 440 mg CaCl2 and was incubated at 37 °C for 20 min. After sonication, the sample was centrifuged at 192,000× g for 1 h at 4 °C to separate the core particle (pellet) from released VP6 proteins (supernatant). The supernatant was dialyzed against distilled water at 4 °C. After concentration by evaporation with a gentle stream of air, protein concentration was determined and 10 µg was radioiodinated as described above. SDS PAGE and autoradiographic visualization of separated radioactive proteins was performed using standard techniques as previously described [Virus (TLP) radiolabeling with escribed ,25. Viraescribed  with humescribed . Brieflyescribed . 125I-labeled rotavirus (TLP) binding to immobilized gangliosides (0.5–10 nmol) or neoglycolipids ) was measured using a thin-layer plate overlay assay as previously described [2O . The plate was developed in chloroform-MeOH-H2O (55:45:10), and after it was air dried, overlay of the 125I-labeled rotavirus was performed by a modification of a previous method [7dpm  of 125I-labeled rotavirus (TLP)/100-cm2 plate, and gently rocked for 2.5 h at 4 °C. The 125I-rotavirus overlay was removed by aspiration, and the plate was rinsed seven times in 400 mL of ice-cold filtered TNC. After air drying for 1 h at room temperature, the plate was wrapped in plastic, placed in a Cronex Lightning Plus cassette with intensifier screens, exposed to Kodak X-Omat film at −80°C for 4 h, and developed in an automatic developer. Measurement of s method . The devVirus focus forming unit (FFU) assays were performed using confluent monolayers of MA104 cells in 24 well plates as previously described . Briefly3 to 1 × 105 focus forming units (FFU)/mL MEM per os. Another set of piglets from the same litter was orally inoculated with the identical virus doses as the first set but including 1–2 µmol SLPE/mL MEM (in separate experiments) either as a single dose or by continuous feeding (every 12 h). All piglets were dosed within 2 h of birth. The piglets were then returned to their respective sow and littermates housed in separate crates (for SLPE versus control (MEM) fed groups), but in the same farrowing room, for the remainder of the experiment. This experimental design was used in an effort to mimic the environment found in commercial pig production facilities. Fecal material from each piglet was collected by anal swab 24–96 h after initial virus inoculation and enzyme linked inmunoassays (ELISA), for detection of rotavirus antigen (group A-specific), were performed on the collected fecal material using an IDEIA kit  according to manufacturer’s instructions. In some experiments, piglets were euthanized at various times postinoculation, intestinal contents collected, and sections of small intestine were processed for immunohistochemistry to localize rotavirus antigen as previously described [Term pregnant normal, rotavirus antibody negative sows  were induced to labor approximately 18 h prior to farrowing. Before the newborn piglets were allowed to nurse, one group from the litter was inoculated with rotavirus doses ranging from 1 × 10escribed . Sows we3, particularly N-glycolylGM3, ganglioside serves as a primary intestinal receptor for porcine Group A (OSU) rotavirus. In addition, we demonstrated the binding affinity for free sialyllactose, the virus binding epitope of GM3, was three orders of magnitude lower than for the intact ganglioside [3, ganglioside receptor, by substituting the sphingosine lipid moiety of GM3, which is not directly involved in virus binding, with a readily-available lipid such as phosphatidylethanolamine that contains a reactive functional group, e.g., an amino group. We previously hypothesized the function of the lipid moiety of GM3, relative to its ability to inhibit rotavirus infectivity of host cells, is to enable presentation of the sialyllactose virus-binding epitope in multivalent form in aqueous media. This multivalent presentation is likely responsible for the observed increased virus binding avidity of GM3 compared to free sialyllactose [Our earlier results  demonstrglioside . Based ollactose . Accordillactose ,38. Characterization of the reductive amination product by thin-layer chromatography (TLC) of aliquots, taken at various times during the reaction, show clear development of a major primulin (lipid) and resorcinol  staining band . Also, cFinally, low resolution FAB mass spectroscopy of the purified SLPE fraction yielded a parent ion of 1308.3 with corresponding sodium salt peaks of 1330.3, 1352.3, and 1374.3 A. This pN-acetylation. Although, the impact of N-acetylation on SLPE function as a receptor mimetic was not further explored in this study, it may be worthwhile in future studies to examine additional SLPE derivatives in attempts to further enhance rotavirus binding affinity. Rotavirus also bound to both LPE and acetyl-LPE, although this binding appeared weaker than to SLPE. The binding to LPE derivatives is likely due to the asialoganglioside specific binding activity of rotavirus double layered particles [To determine if rotavirus was able to recognize either SLPE or LPE we used TLC overlay binding assay as described in the Experimental Section. Rotavirus bound to SLPE in a concentration-dependent manner A. Interearticles  which we3 ganglioside (50) was approximately 15 µM for SLPE as compared to 5 µM for GM3. No inhibition of virus binding was observed for LPE, the neoglycoprotein sialyllactoseBSA, or PE. SLPE displayed dose-dependent inhibition of both rotavirus binding and infectivity of MA104 cells that was comparable to native GMglioside . SLPE in1 . PE showed no significant inhibition of virus infectivity . The mec1 C. These 1 B, may in1 . in vivo, relative large amounts (~90 mg) of SLPE were produced to test as a nutriceutical for protection against rotavirus disease at the time of virus infection in neonatal piglets. In the first experiment, each piglet received either 1.0 µmol SLPE in MEM, or MEM alone, as a single dose per os at the time of virus inoculation. The presence of clinical signs was monitored for 88 h post-inoculation (PI) and virus shedding was measured at 40 h, 64 h, and 88 h as described in the Experimental Section. In the second and third experiment, each piglet was dosed with SLPE or MEM at the time of virus inoculation as described above and then again every 12 h for up to 96 h at which time all piglets were euthanized. Clinical signs, virus shedding and immunohistochemical detection of rotavirus in intestinal sections harvested from euthanized piglets were analyzed as described in the Experimental Section. The comparison of the amount of rotavirus shed in feces of experimental (+1.0 µmol SLPE) and control piglets (MEM only), at 40 h, 64 h, and 88 h post infection with varying amount of virus (1 × 103–1 × 105 FFU), is shown in For experiments aimed at testing the ability of the SLPE to block rotavirus infection 5 FFU). This first experiment was designed to determine optimal virus dose and initially evaluate whether SLPE afforded any protection against virus shedding and diarrhea. SLPE-treated piglets did not develop clinical signs of rotavirus disease  compared to their littermates receiving only MEM, who developed watery diarrhea, fecal staining, huddling behavior, and anorexia beginning 24 h post-inoculation. Although virus shedding was observed in piglets receiving a single dose of SLPE it was markedly  reduced in SLPE fed piglets 40 h PI . Virus s5 FFU virus alone) and 9 experimental piglets (inoculated with 1 × 105 FFU plus a single dose of SLPE (1 µmol)) were maintained on separate sows but in the same farrowing house. All control piglets displayed a positive fecal ELISA  compared to none of the SLPE-treated piglets  at 24 h post inoculation. At 48 h post inoculation; however, 6/9 SLPE-fed piglets had positive fecal ELISA values. Together, the results of these two experiments indicated a single dose of SLPE provided some initial protection against rotavirus infection, as evidenced by the delay in virus shedding in feces, but was not able to provide sustained protection. In a subsequent experiment, 11 control piglets  would afford greater protection against rotavirus infection and disease. When SLPE (1 µmol) was fed every 12 h post-inoculation for the duration of the experiment, virus shedding in feces was not detected in any of the experimental piglets . In contIn the fourth experiment, SLPE (2 µmol) was continuously fed (every 12 h) for 96 h as described above. Again, rotavirus disease and virus shedding were not detected in piglets fed SLPE as compared to control piglets inoculated with virus alone . In the Finally, rotavirus infection was clearly evident following immunohistochemical staining of intestinal tissue harvested from control virus-infected piglets, but not in virus-inoculated piglets continuously fed SLPE . In piglOur findings demonstrate a dramatic reduction in virus shedding and absence of rotavirus disease in SLPE-fed piglets, thus providing “proof of concept” that a nutriceutical approach of using natural or synthetic receptor mimetics, such as SLPE, hold substantial promise for the prevention of rotavirus disease. This approach may be applicable not only to piglets in a natural field setting, but also as a potential dietary supplement, for example in infant formulae, for the prevention of rotavirus or other gastrointestinal infectious diseases in human infants.


LIG4. The p.S205LfsX29 mutation results in lack of the nuclear localization signal and appears to be a null mutation. The second mutation p.K635RfsX10 lacks the C-terminal region responsible for XRCC4 binding and LIG4 stability and activity, and therefore this mutant might be a null mutation as well or have very low residual activity. This is remarkable since Lig4 knockout mice are embryonic lethal and so far in humans no complete LIG4 deficiencies have been described. This case broadens the clinical spectrum of LIG4 deficiencies.DNA double-strand break repair via non-homologous end joining (NHEJ) is involved in recombination of immunoglobulin and T-cell receptor genes. Mutations in NHEJ components result in syndromes that are characterized by microcephaly and immunodeficiency. We present a patient with lymphopenia, extreme radiosensitivity, severe dysmaturity, corpus callosum agenesis, polysyndactily, dysmorphic appearance, and erythema, which are suggestive of a new type of NHEJ deficiency. We identified two heterozygous mutations in  DCLRE1C (MIM #605988), PRKDC (MIM #600899), NHEJ1 (MIM #611290), and LIG4 (MIM #601837) [Moshous et al., The non-homologous end joining (NHEJ) pathway is involved in the repair of the DNA double-strand breaks. These can be generated during DNA replication, exposure to exogenous agents such as ionizing radiation (IR), or physiologically during V(D)J recombination, as happens during the early stages of B- and T-cell differentiation to generate antigen-specific B- and T-cell receptors. Defects in NHEJ factors result in IR sensitivity, and in defects in V(D)J recombination leading to immunodeficiency. Genetic defects have been described in several NHEJ genes, including Pseudomonas aeruginosa and Enterococcus faecalis urinary tract infection, respectively, and he tested positive for P. aeruginosa, P. jiroveci, rhinovirus, norovirus, astrovirus, Clostridium difficile, and Candida. Besides the infectious complications, the first 3 months of life were characterized by feeding difficulties, diarrhea, failure to thrive, cholestatic icterus, tubulopathy, generalized erythema, and very dry cracked skin. Initially the patient seemed to recover from the opportunistic infections, but a second episode of an acute sepsis-like syndrome with respiratory insufficiency complicated by severe gastrointestinal bleeding—probably due to the development of thrombocytopenia—could not be successfully treated; the patient died at the age of 6 months.The patient was born with extreme dysmaturity after 37 weeks of gestational age. At the age of 3 months, his height was 43 cm (−7.4 SD), weight was 1870 g (−8.9 SD), and head circumference was 29 cm (−8.9 SD). Besides the dysmaturity, the patient had several dysmorphisms . The increase in the number of T cells was mainly caused by an increase in the CD8+ T cells probably related to a viral infection. The presence of maternal T cells was excluded. Immunoglobulin (Ig) G was decreased, which was not secondary to malabsorption, whereas IgM and IgA were normal (Supp. Table S2) and Ig substitution therapy was initiated at the age of 4.5 months.The clinical presentation, especially the immunodeficiency together with microcephaly was suggestive for a NHEJ defect. Therefore, the patient's fibroblasts were tested in a clonogenic survival assay . These were extremely IR sensitive by an order of magnitude, c.f. the control at 10% survival  showed the presence of two heterozygous single-nucleotide deletions in the LIG4 gene (c.613delT and c.1904delA) (submitted to http://www.lovd.nl/LIG4). The first deletion was inherited from the mother and resulted in a frameshift and a premature stop codon in the DNA-binding domain (p.S205LfsX29). This mutation was recently described in the LIG4 patient presenting with the Dubowitz syndrome [Yue et al., Sequencing of the omain p.S05LfsX29.635K636V637I638 → R635K636L637L638) without affecting the charge, and a premature stop codon (p.K635RfsX10). In this mutant, part of the NLS is retained, but it lacks both BRCT motifs and the XRCC4-binding site, which are necessary for the interaction with Cernunnos/XLF [Critchlow et al., The second paternally inherited deletion resulted in a frameshift, changing the last four amino acids of the NLS . The p.R814X mutant lacks the BRCT 2 motif, but the NLS and XRCC4-binding site are present [Ben-Omran et al., In our overexpression system, this mutant was still expressed in the nucleus Fig. B and is


Phylogenetic studies have largely contributed to better understand the emergence, spread and evolution of highly pathogenic avian influenza during epidemics, but sampling of genetic data has never been detailed enough to allow mapping of the spatiotemporal spread of avian influenza viruses during a single epidemic. Here, we present genetic data of H7N7 viruses produced from 72% of the poultry farms infected during the 2003 epidemic in the Netherlands. We use phylogenetic analyses to unravel the pathways of virus transmission between farms and between infected areas. In addition, we investigated the evolutionary processes shaping viral genetic diversity, and assess how they could have affected our phylogenetic analyses. Our results show that the H7N7 virus was characterized by a high level of genetic diversity driven mainly by a high neutral substitution rate, purifying selection and limited positive selection. We also identified potential reassortment in the three genes that we have tested, but they had only a limited effect on the resolution of the inter-farm transmission network. Clonal sequencing analyses performed on six farm samples showed that at least one farm sample presented very complex virus diversity and was probably at the origin of chronological anomalies in the transmission network. However, most virus sequences could be grouped within clearly defined and chronologically sound clusters of infection and some likely transmission events between farms located 0.8–13 Km apart were identified. In addition, three farms were found as most likely source of virus introduction in distantly located new areas. These long distance transmission events were likely facilitated by human-mediated transport, underlining the need for strict enforcement of biosafety measures during outbreaks. This study shows that in-depth genetic analysis of virus outbreaks at multiple scales can provide critical information on virus transmission dynamics and can be used to increase our capacity to efficiently control epidemics. Outbreaks of highly pathogenic avian influenza (HPAI) viruses have affected poultry worldwide in the last decades, resulting in vast socioeconomic damages and many human infections. It is important to determine the route of transmission between poultry farms to be able to implement efficient control measures. Here, we investigate possible use of sequence data to unravel the route of virus transmission during an HPAI H7N7 epidemic that took place in 2003 in the Netherlands. We obtained virus sequence data from most of the outbreaks during the epidemic, and found a high level of genetic diversity driven by a rapid evolutionary rate of HPAI H7N7 virus. The phylogenetic inference of the inter-farm transmission network turned out to be difficult due to the presence of potential reassortant virus strains, multiple mutations at highly variable sites and within farm virus diversity. However, most virus samples could be grouped within clearly defined and chronologically sound clusters of infection, giving us valuable insights on the diffusion of the virus during the outbreak. We discuss the implications of the results obtained for the evolutionary and epidemiological dynamics of avian influenza viruses and disease control. Highly pathogenic avian influenza (HPAI) viruses represent a major concern for public health and global economy, as outbreaks in the last decades resulted in vast socioeconomic damages and numerous human infections. Thanks to increasing availability of avian influenza virus sequence data and the development of new computational and statistical methods of analysis, phylogenetic studies have largely contributed to a better understanding of the emergence, spread and evolution of HPAI epidemics The epidemic of HPAI H7N7 in the Netherlands in 2003 represents a unique opportunity to study the epidemiological and evolutionary processes involved in HPAI transmission dynamics in detail. This epidemic started in the most poultry-dense area of the Netherlands  on February 28, 2003. Despite implementation of control measures, the outbreak spread across the entire Gelderland area as well as in a contiguous central region with a lower density of poultry farms. New outbreaks were reported in April in the Limburg province, another poultry-dense area in the South of the Netherlands, in Germany and in Belgium The H7N7 virus was sampled from the majority of the 255 farms infected, but, to date, only little genetic data have been published from this epidemic Virus RNA was extracted from homogenized trachea tissue samples from dead chickens (5 chickens per sample) obtained from 184 of the 255 farms infected during the H7N7 outbreak , but a strand of 52 to 74 nucleotides in the NA stalk region was also found deleted in 13 samples from the Limburg area, with a total of 7 different types of deletions, 3 of which resulted in a frame shift in the NA coding sequence . In tota−2 and 1.02×10−2 substitutions per site per year (substitutions/site/year), respectively; −2 substitutions/site/year). These estimates were associated with large 95% highest posterior density intervals  of the HPAI H7N7 viruses were estimated separately for the three gene datasets using a Bayesian Markov Chain Monte Carlo (BMCMC) method als HPD; . TMRCA eals HPD; . Again, als HPD; , showingPhylogenetic trees of the HPAI H7N7 virus sequences were reconstructed for the three separate HA, NA and PB2 sequence datasets using Bayesian Inference and Maximum Likelihood methods . For eacth week of the epidemic.To assess the inter-farm transmission network, we manually concatenated the HA, NA and PB2 sequences for all virus samples, and used this single alignment to construct a Median Joining phylogenetic network We identified 15 pairs of farm samples that uniquely shared identical sequence genotypes, representing likely transmission events . Furtherω  = dN/dS) in the different datasets using in CODEML ω <1), with PB2 under the strongest negative natural selection . We further tried to identify sites under positive selection in the three genes using the single-likelihood ancestor counting (SLAC), the random effect likelihood (REL), and the fixed effect likelihood (FEL) methods Pr>0.95). In addition, it detected 7 amino acid sites under positive selection in the NA dataset .We assessed the selection pressures acting on the three genes by estimating the ratio of non-synonymous to synonymous nucleotide substitutions  on 6 farm samples (5 chickens per sample). We chose 4 samples  and one cluster of closely related viruses (Cluster IV) were identified as potential reassortants due to their discordant position in the phylogenetic trees and the network. However, the signal of reassortment in all sequences was closely associated with signal of positive selection at specific amino acid residues, so the discordances in the phylogenies may be due to convergent evolution driven by the adaptive advantages conferred by these amino acid changes. In all cases, we prefer to consider these farm samples unsuitable for the study of the H7N7 inter-farm transmission dynamics until more is known about these possible reassortment events.Secondly, an important limitation of our genetic dataset is the characterisation of only one virus sequence per farm, whereas each farm  may contain a wide variety of closely related virus variants. Our genetic data could be considered a reliable tool to elucidate the transmission pathways of the HPAI H7N7 between farms if it can be assumed that the virus genotype obtained for each farm samples represents the dominant strain in the farm sample and that this dominant strain is the one most likely to be transmitted to other farms. These assumptions were partially supported by clonal sequencing performed on six farm samples, as the genotype used in our dataset corresponded to the dominant variant in the clone population in 5 out of 6 farms. This dominant variant represented >50% of the clones in 4 samples , suggestImportantly, clonal sequencing of the one farm sample (F191) also showed that the virus strain originally sequenced was not the dominant variant of the farm but was a potentially inactive variant (as it contained a frame shift deletion) present at a low frequency. It suggests that our genetic dataset was not always composed of the dominant genotype in the farm samples, potentially affecting the resolution of the transmission network. The variant with highest frequency in sample F191 represented 17% of the clones, suggesting that the absence of a highly dominant strain may have allowed the sequencing of another variant. This lack of dominance could be due to the production of a high variety of variants with stalk deletion, possibly associated with the evolution of a deletion-prone polymerase in viruses infecting the first farm in the Limburg area (F191). If it is the case, it would suggest that only the 13 samples presenting deletions in our dataset may have been wrongly positioned in the phylogenetic network due to the dominance issue.Most mutations differentiating the multiple genetic variants from the dominant variant in the clone populations were associated with amino acid changes or deletions, suggesting that the virus population within a flock  is composed of strains of variable fitness, with one or few best-fit strains dominating the population. We cannot rule out the possibility that the genetic variation observed in our cloning results is an artefact of RNA manipulation. However, the error rate of the RT polymerase used  was estimated to be 1/15,000 by the manufacturer, so it should not have a major influence on an analysis targeting an 800 bp gene region. Also, the genetic variation we obtained is similar to what has been observed in other avian Influenza viruses using a similar approach Results from the network and the clonal sequencing analysis of F191 showed that some mutations occurred multiple times at different time periods, leading to chronological anomalies in the farm-to-farm connections identified in the phylogenetic network. These anomalies were limited to clusters including Limburg samples, suggesting that the high viral genetic diversity produced during the outbreak in Limburg may be at their origin. Interestingly, reports from officials involved in the control of the epidemic indicate that F191 may have been infected for over a week before being reported and sampled. Also this farm housed >10,000 turkeys, a species shown to play a key role in the evolution of AI pathogenicity in domestic animals Overall, our results suggest that a combination of evolutionary processes, such as multiple mutations at highly variable sites, positive selection, and/or reassortment, drove the genetic diversity observed in the HPAI H7N7. The effect of these processes might have been stronger at the early stages of the epidemic, as farms may have been infected for longer time before control measures were taken (as reported for F191). The long branches and poor quality of connections at the base of the network supports this hypothesis. Despite this complex evolutionary history of the H7N7 virus, most farm samples could be grouped within clearly defined and chronologically sound clusters of infection, giving us valuable insights on the spreading of the virus during the epidemic.et al.Boender et al.Importantly, our results also suggest that a discrete number of long distance transmission events were at the origin of the virus spread into new areas, rather than a slow wave-like movement of the virus towards the south of the country. Notably, it is interesting to note that farm UN167, a back-yard poultry farm, seems to be at the origin of the outbreak in the Limburg area. Conversely, Bavink Samples were collected as part of the diagnosis by veterinarians of the Food and Consumer Product Safety Authority (the Netherlands) and submitted to the Central Veterinary Institute for confirmation by virus isolation. The authors of this study were not involved in sample collection. Viral RNA was directly extracted from 184 infected trachea tissue samples from dead chickens (5 chickens per sample) using a High Pure Viral RNA extraction kit . Complementary DNA was synthesized by reverse transcription reaction using SuperScript III , and gene amplification by PCR was performed using the PCR Expand high fidelity kit  and primers specific for the hemagglutinin (HA), neuraminidase (NA) and basic polymerase 2 (PB2) gene segments. Sequencing was performed by using the BigDye Terminator v. 1.1. sequencing kit  and an ABI Prism 3130 genetic analyzer (Applied Biosystems). Primers and PCR protocols are detailed in Sequences were aligned using BIOEDIT epsilon, which controls the level of homoplasy, was set at the same value as the weight of characters used to calculate the genetic distances . The average number of nucleotide differences within and between the phylogenetic clusters identified was calculated with MEGA Additional methods were used to infer the phylogenetic relationships from the HA, NA and PB2 datasets. A Bayesian MCMC inference method was performed in MRBAYES Homologous recombination within each gene segment was searched using Recombination Detection Program version 2 (RDP2) ω = dN/dS) using codon-based phylogenetic methods implemented in CODEML (available in the PAML package ω<1) or model M2a of positive selection  was a statistically better fit to the data Selection pressure on the HA, NA and PB2 genes was investigated by estimating the ratio of non-synonymous to synonymous nucleotide substitutions (PCR amplification targeting a 850 bp portion of the NA gene (bases 57–908) was performed on cDNA obtained from five samples  using the PCR Expand high fidelity kit (Roche Diagnostics). An additional PCR was used to amplify a 570 bp portion of the HA gene (bases 81–650) on the two samples from Limburg only . Primers and PCR protocols are described in Figure S1Time-scaled phylogenies  inferred using Bayesian MCMC analysis from (A) HA gene; (B) NA gene; (C) PB2 gene. Nodes supported by >0.7 posterior probability are indicated by a grey dot. Posterior probability values from the time-scaled BMCMC method, the MrBayes BMCMC method, the Maximum Likelihood method  are also indicated (tsBMCMC/MrBMCMC/ML). Samples sharing identical HA, NA, and/or PB2  are listed in (TIF)Click here for additional data file.Figure S2Time-scaled median-joining phylogenetic network of H7N7 viruses. This network is identical to (TIF)Click here for additional data file.Figure S3Bootscan recombination analysis on the full dataset of concatenated H7N7 virus sequences. Sequences obtained from (A) F45, (B) F76, and (C) F143 were used as query in the analysis, with a 800 bp window size and step size of 10 bp. A schematic diagram of the concatenated HA, NA and PB2 virus segments is shown on top.(TIF)Click here for additional data file.Table S1Description of the H7N7 virus samples used in this study.(DOC)Click here for additional data file.Table S2Summary statistics of the BMCMC analyses.(DOC)Click here for additional data file.Table S3List of farm isolates sharing identical HA, NA and/or PB2 sequences. Group names refer to names given in phylogenetic trees in (DOC)Click here for additional data file.Table S4List of primers and protocols used for PCR amplification and sequencing of HA, NA and PB2 genes.(DOC)Click here for additional data file.