Ralstonia solanacearum encodes type III effectors, called GALA proteins, which contain F-box and LRR domains. The GALA LRRs do not perfectly fit any of the previously described LRR subfamilies. By applying protein sequence analysis and structural prediction, we clarify this ambiguous case of LRR classification and assign GALA-LRRs to CC-LRR subfamily. We demonstrate that side-by-side packing of LRRs in the 3D structures may control the limits of repeat variability within the LRR subfamilies during evolution. The LRR packing can be used as a criterion, complementing the repeat sequences, to classify newly identified LRR domains. Our phylogenetic analysis of F-box domains proposes the lateral gene transfer of bacterial GALA proteins from host plants. We also present an evolutionary scenario which can explain the transformation of the original plant LRRs into slightly different bacterial LRRs. The examination of the selective evolutionary pressure acting on GALA proteins suggests that the convex side of their horse-shoe shaped LRR domains is more prone to positive selection than the concave side, and we therefore hypothesize that the convex surface might be the site of protein binding relevant to the adaptor function of the F-box GALA proteins. This conclusion provides a strong background for further functional studies aimed at determining the role of these type III effectors in the virulence of R. solanacearum.The phytopathogenic bacterium  The coils are arranged so that all the strands and helices are parallel to a common axis, resulting in a non-globular, horseshoe-shaped molecule with a curved parallel β-sheet lining the inner circumference of the horseshoe and the helices flanking the outer circumference. In LRR proteins, a six-residue motif LxxLxL is conserved , and in the known structures corresponds to a turn and a consecutive β-strand; whereas the remaining parts of repeats may be very different. While the invariant motif of the β-region is a characteristic feature of the entire LRR superfamily, the consensus sequences of the variable part suggest several specific subfamilies. LRR proteins can be subdivided into at least seven subfamilies Leucine-rich repeats (LRRs) are 20–29-residue sequence motifs present in a number of proteins with diverse functions Since 1998, when these conclusions were formulated, a large number of new LRR proteins have been identified and several new 3D structures of LRR proteins have been determined Ralstonia solanacearum encodes several type III effectors, called GALA proteins, that contain F-box and LRR domains R. solanacearum GALA-LRRs there is the Cysteine-Containing LRR (CC-LRR) subfamily of plant, animal and fungi proteins which can also contain the F-box domains and, therefore, may have a similar function. Thus, it was not clear, whether the GALA-LRR proteins are members of the CC-LRR subfamily or they should be assigned to a new LRR subfamily. Here we clarify this ambiguous case by using sequence analysis and molecular modeling. We also focus our analysis on the origin and evolution of GALA proteins from R. solanacearum.Recently, it was shown that the phytopathogenic bacterium Ralstonia solanacearum shows that their 24-residue long LRRs have a specific consensus pattern that has characteristic differences , protists  and animals . Interestingly, some of the GL-LRR proteins from plant, animal and protista also contain F-box domains.Using the generalized profile technique R domain . Some prR domain . RemarkaR domain . Sequencvia their LRRs, to the SCF-type E3-ubiquitin ligase complex Although, the newly identified GALA-LRRs and GL-LRRs do not perfectly fit any of the previously described consensus sequences of seven LRR subfamilies Parachlamydia sp.), protista (Dictyostelium) and fungi . The sequence profiles and search results can be viewed on a dedicated web-page http://bioinfo.montp.cnrs.fr (Tools>Profiles>Show Profiles). Interestingly, about 600 of them have an F-box domain. This strongly supports a similar role for these specific LRRs in binding the protein substrate that is then recruited by the SCF-type E3-ubiquitin ligase.On the assumption of the membership of GALA and GL-LRRs in the CC-LRR subfamily, the previously proposed CC-LRR consensus Ralstonia solanacearum . In The knowledge of even one 3D protein structure in a given sequence alignment provides a powerful means to test the correctness of the whole alignment. In our case, the 3D structure of one CC-LRR protein, the human F-box protein Skp2 is known The modeling also shows that GALA-, GL-, and CC-LRRs can be packed well together and therefore, in contrast to the other LRR subfamilies, do not have mutually exclusive relationships with CC-LRRs in terms of inter-LRR packing . This cohttp://www.ncbi.nlm.nih.gov/entrez). In order to dissipate any doubt, It is worth mentioning that GALA-LRRs are erroneously assigned to the RI-LRR subfamily in the annotation of protein databases on the NCBI Web site  and in 9 proteobacteria out of 184 complete sequences available . All these positive hits correspond indeed to the presence of a canonical F-box domain. The evidence for functional F-box domains is available for both A. tumefaciens and R. solanacearum F-box containing proteins Borrelia burgdorferi, B. garinii, Chlamydophila caviae, Rhizobium etli, Salmonella tiphimurium and Streptococcus pneumoniae) were inspected and clearly ruled out as being F-box domains  for the presence of the F-box domain (automatic search with Pfam Hiden Markov Model for F-box (PF00646) service available at TIGR CMR). We only found F-box domains present in one chlamydiae species out of 11 complete sequence available . It is interesting to mention that all the bacteria containing F-box domains in their genome intimately interact with eukaryotes. For example, P. amoebophila, S. glossinidius and M. loti are symbionts of amoeba, insects and plants; A. tumefaciens, R. Solanacearum, P. syringae, X. campestris and X. axonopodis are plant pathogens and C. burnetii and L. pneumophila are human pathogens. Finally, for several of these F-box-containing bacterial proteins injection into their host cells  has been proven  L. pneumophilae) The F-box domain has its only described function in eukaryotic cells and is overrepresented in this kingdom (interpro F-box domain (IPR001810) hits: 735 in GALA genes from the R. solanacearum genome , GALA1(RSp0914) is located in an alternative codon usage region, GALA2(RSp0672) is flanked by a region duplicated elsewhere in the genome and GALA3(RSp0028) is flanked at either side by an alternative codon usage region. These genomic characteristic have been previously identified as potential signatures of LGT R. solanacearum to uptake DNA Among the seven R. solanacearum GALA genes clustered together and with Arabidopsis thaliana or with Oryza sativa as their closest basal lineages (for a representative example of an inferred Maximum Likelihood (ML) tree see www.phylosoft.org/atv/). Only in some rare cases we also observed that one or two GALA genes were grouped with a non-plant lineage (but with low clade supports). Overall, the underlying phylogenetic signal appears to be in favour of the postulated LGT from a plant lineage. At the same time, the limited accuracy of inference does not enable us to confidently suggest a putative donor.One way of testing such a hypothesis is through phylogenetic analysis of the protein origins to identify putative donor for a potential LGT. Apart from the F-box domain, the F-box-containing proteins are constituted of repeat domains (mostly LRRs). Thus phylogenetic inference on the whole protein for large numbers of divergent taxa appears highly problematic. Instead we focused the analysis on the F-box domain, using 50 aa on their own, as well as together with 150 aa from the downsteam F-box-adjacent region or a shorter region containing 2 or 3 LRRs. Fifteen large datasets were assembled to include homologues from the broadest possible species range. The datasets varied by the similarity thresholds used in the profile searches Gemmata sp., Parachlamydia sp., Legionella pneumophila, Rhodopirellula baltica, Ralstonia solanacearum), protista  and fungi , among which many are parasitic organisms colonizing plants and animals.Our conclusion that the GALA-LRRs belong to the CC-LRR subfamily is consistent with the hypothesis of the lateral transfer. The updated CC-LRR subfamily has proteins from a very heterogeneous group of organisms including animals, plants, fungi, protista, and bacteria. By its wide taxonomic distribution it resembles the TpLRR subfamily visa versa  and the Bayesian prediction P-values <0.01). Estimates suggested that 8% of sites evolved under positive selection. For GALA2 LRRs, the Bayesian approach detected positions 8 and 15  was analyzed and none of the tests gave a significant evidence for positive selection, although parameter estimates hinted that this possibility could not be ruled out. This could mean that only for some GALAs the LRRs accumulated changes due to positive selection, as by averaging over all domains we loose power to detect positive selection affecting only certain GALA proteins. To test this we subdivided the aligned LRR sequences, so that only sequences from the orthologous GALAs were analyzed together. Parameter estimates from these alignments showed that for all GALA proteins 50–70% of the LRR positions are rather conserved while substitutions at remaining sites generally have neutral effect on the fitness of the protein. However for GALA2 both LRTs for positive selection were highly significant , but the estimate of the ω ratio (describing selective pressure) was only slightly higher than 1 (ω≈1.15), indicating the lack of clear support for positive selection signal. Model M1a that does not allow positive selection described data equally as well as model M2a that allows positive selection. The Bayesian inference suggested that positions 4, 8, 11, 15 and 17 had a slightly elevated ratio of nonsynonymous to synonymous changes. Changes at these sites at the very least should be neutral to the fitness of the protein but may have a mild advantageous effect, possibly indicating a recent increase of adaptive pressure. The same can be concluded about position 4 in GALA1 and GALA3 LRRs and position 11 in GALA5 LRRs. If mapped on the structural model of the GALA-LRR, most of them  are located on the external side of the α-helix and on the convex surface of the LRR solenoid. The side-chain in position 4 belongs to the loop connecting β-strand with the α-helix and also is exposed to the solvent , providing the evidence of positive selection on both genes. The lack of the strong evidence for positive selection in GALA7 LRRs in the previous analysis suggests that positive selection may affect only certain (orthologous) repeats of GALA7 while the homologous sites in other repeats of this protein evolve neutrally. In this last analysis the number of sequences is too low for the Bayesian prediction to be accurate, and so the results of such inference are used only in an explorative manner, to see if the predicted positive selection sites correspond to any particular repeats and where such sites could be located. Mapping of the predicted sites of GALA2 onto the repeats of the LRR domain (with probability >0.85 from BEB) shows that they are located in position 15 in four LRRs and in position 21 of one LRR and dispersed over the LRR domain mostly on the convex surface  genes into a R. solanacearum ancestral recipient strain. We further looked into the GALA-LRR in all the GALA sequences available and found that for some GALA proteins there is a strong signature of positively selected residues and only on the convex side of the GALA-LRR structure. This suggests that the GALA proteins, probable E3-ubiquitin ligase adaptors, necessary for the virulence of R. solanacearum on its host plants, could bind their potential protein ligand on the convex side of the LRR domains, similarly to the A. thaliana TIR1 F-box type E3 ubiquitin ligase The pftools package ftp://ftp.ncbi.nih.gov/blast/db). The sequence profiles and results of the search can be viewed on a dedicated web-page http://bioinfo.montp.cnrs.fr/profiles (Tools/Profiles/Show Profiles).The generalized sequence profile method and the The initial template for GALA-LRRs was taken from a 24-residue LRR (residues 2211 to 2235) of the known crystal structure of human Skp2 protein To examine the side-by-side packing of LRRs from different subfamilies the following procedure was used. First, fragments of the LRR domains corresponding to different LRR subfamilies were extracted from the known crystal structures . Second, each of these structures and the structural model of GALA-LRRs were superimposed with CC-LRR domain. For the superposition, the conserved β-structural parts of the LRRs were used. Two adjacent β-strands of CC-LRR and the analyzed structures were superimposed and the side-by-side packing of the variable LRR fragments was analyzed.ω = dN/dS, with ω<1, = 1, or >1 indicating conserved, neutral or adaptive evolution respectively t as P(t) = exp(Qt). The generator matrix Q = {ijq} defines the instantaneous substitution rates at site s from codon i to codon j :The selective pressure at the protein level was measured by the ratio of nonsynonymous to synonymous rates jπ is the frequency of codon j, parameter κ is the transition/transversion ratio, and ωs) for positive selection compares maximum log-likelihoods of two nested models, one of which allows sites under positive selection while another does not. To test that a model allowing positive selection describes data significantly better, twice the log-likelihood difference is compared to the χ2-distribution with degrees of freedom equal to the difference in the number of free parameters between the two models. We performed two LRTs for positive selection, comparing models M2a and M8 that allow sites with ω>1  with simpler models M1a and M7 respectively that do not allow sites with ω>1 (null hypotheses). Model M1a  assumes two site classes in proportions p0 and p1 = 1–p0: one with ω0 ratio estimated between 0 and 1, and the other with ω1 fixed at 1. The alternative model M2a (positive selection) extends the null model M1a by adding a proportion p2 of positively selected sites with ω2>1, estimated from data. The second LRT uses the null model M7 (beta) that assumes the ω ratio is drawn from a beta distribution defined between 0 and 1. The alternative model M8 has an extra class of sites under positive selection with ω>1.The models used in the analysis differed by statistical distributions of the ω is assumed to be constant over all sites in the sequence, and the discrete model M3 that allows three discrete classes of sites with ratios ω0, ω1, and ω2 occurring in proportions p0, p1 and p2 = 1−p0−p1. Models M0 and M3 are also nested, and can be used to perform the LRT for heterogeneity of selective pressure along the sequence We also considered two other codon models: the most simple one-ratio model M0, where et al. Where a LRT for positive selective pressure was significant, we used the Bayesian inference to calculate posterior probabilities that a site belongs to a particular site class. The posterior distribution of the parameter of interest (in our case ω) is proportional to the product of its assumed prior distribution and the likelihood of the observed data given this prior. In this study we used the Bayesian Empirical Bayesian approach All ML phylogenies were inferred using PHYML program Table S1Maximum likelihood estimates of selection parameters for codon models(0.06 MB DOC)Click here for additional data file.Figure S1www.phylosoft.org/atv/Phylogenetic tree supplemental file phymlGALA.tre, which can be viewed with ATV-forester from (0.04 MB TXT)Click here for additional data file.Figure S2Positions of positive selection in GALA2(0.03 MB DOC)Click here for additional data file.Figure S3Positions of positive selection in GALA2(0.02 MB DOC)Click here for additional data file.


Penicillium digitaum, have a considerable economic impact. However, little is known about the molecular processes underlying the response of citrus fruit to P. digitatum.Postharvest losses of citrus fruit due to green mold decay, caused by the fungus P. digitatum. Sequence annotation of clones from the subtracted cDNA library revealed that induction of secondary and amino acid metabolisms constitutes the major response of citrus fruits to P. digitatum infection. Macroarray hybridization analysis was conducted with RNA from either control, wounded, ethylene treated or P. digitatum infected fruit. Results indicate an extensive overlap in the response triggered by the three treatments, but also demonstrated specific patterns of gene expression in response to each stimulus. Collectively our data indicate a significant presence of isoprenoid, alkaloid and phenylpropanoid biosynthetic genes in the transcriptomic response of citrus fruits to P. digitatum infection. About half of the genes that are up-regulated in response to pathogen infection are also induced by ethylene, but many examples of ethylene-independent gene regulation were also found. Two notable examples of this regulation pattern are the genes showing homology to a caffeine synthase and a berberine bridge enzyme, two proteins involved in alkaloid biosynthesis, which are among the most induced genes upon P. digitatum infection but are not responsive to ethylene.Here we describe the construction of a subtracted cDNA library enriched in citrus genes preferentially expressed in response to pathogen infection followed by cDNA macroarray hybridization to investigate gene expression during the early stages of colonization of the fruit's peel by P. digitatum infection, emphasizing differences and commonalities with those triggered by wounding or exogenous ethylene treatment. Interpretation of the differentially expressed genes revealed that metabolism is redirected to the synthesis of isoprenes, alkaloids and phenylpropanoids.This study provided the first global picture of the gene expression changes in citrus fruit in response to  Penicillium digitatum, the causal agent of green mold, is the major pathogen of citrus fruit worldwide during postharvest storage. Control of this fungus is mostly based on the use of chemical fungicides, such as imazalil or thiabendazol. However, problems associated with the use of these compounds are leading to the development of new and safer control alternatives, which mostly rely on biological control microorganisms, physical or chemical treatments either as standalone or combined treatments. Another approach focuses on improving the natural defense capability of the fruit. However, despite the economic relevance of losses due to P. digitatum infection, there have been few studies directed to unravel citrus fruit responses to pathogen invasion or to elicitors that increase resistance against pathogen infection.Citrus is one of the most economically important fruit crops in the world. Harvested fruits are usually stored before they reach the market for fresh consumption. During this postharvest period fruits are subjected to both biotic and abiotic stress conditions. P. digitatum than the albedo (inner white part)  dCTP-labelled single-strand cDNAs were synthesized from 20 μg of total RNA by reverse transcription using anchored oligo(dT)20VN primer and Superscript III Reverse Transcriptase (Invitrogen) following standard protocols. The incubation was allowed to proceed for 120 minutes at 50°C. RNA was degraded by alkaline lysis, and subsequently samples were neutralized. Unincorporated [α-33P] dCTP was removed with MicroSpin S-300HR columns . 33P incorporation was quantified via liquid scintillation. The final concentration of labelled cDNA was adjusted to 3 × 106 dpm/ml with TE. dATP by using the Strip-EZ PCR Kit (Ambion). Prehybridization and hybridization were performed with ULTRAhyb hybridization buffer (Ambion) at 42°C following the manufacturer's instructions. Filters were washed once for 10 min with 2% SSC and 0.1% (w/v) SDS at 42°C, once for 30 min with 2X SSC, 0.1% (w/v) SDS at 55°C, and twice for 30 min with 0.1X SSC, 0.1% (w/v) SDS at 55°C. Membranes were then exposed to an imaging plate  for different periods of time. Hybridization signals were recorded with a FLA-3000 laser scanner (FujiFilm) and assessed with the software Image Gauge 4.0 (Fuji Film). Probes were stripped off using the Strip-EZ PCR Kit (Ambion) following the manufacturer's instructions.Total RNA was electrophoresed through a formaldehyde gel and transferred to a Hybond NPST constructed the subtracted library and prepared amplicons for spotting. LGC, SA and JFM conducted fruit experiments, sequencing and macroarray and Northern hybridizations. LGC and JFM analyzed the data. LGC, SA and JFM draft the manuscript. LGC, JFM and LZ conceived and supervised the work. All authors read and approved the final manuscript.P. digitatum (I)Macroarray hybridization results from 'Navelina' oranges treated with air (A) or with 10 ppm of ethylene (E) for 16 h, or 24 h after wounding (W) or inoculation with .Click here for fileSequence annotation of RindPdigS clones.Click here for fileP. digitatum infected 'Navelina' fruits at different time points after inoculationNorthern blots analysis of RindPdigS genes in control, wounded or . In brackets it is indicated whether the clone is a singleton or the cluster it belongs to Hybridization with the C. sinensis 26 S rDNA is shown in the bottom panel. Normalization of hybridization signals was carried out with respect to the hybridization signal of the C. sinensis rDNA. Values below the panels show the relative quantification of the corresponding hybridization signal referred to the value of the infected sample at 24 hpi. Those hybridization signals lower than two folds the intensity of background were not assessed (-).Click here for fileC. sinensis Navelate fruit's peel after ethylene or 1-MCP pretreatmentNorthern blot analysis of clones belonging to RindPdigS in . Tissue samples were analysed before any treatment (C0) or after 16 h of treatment with air (A), 500 ppb xof 1-MCP (M), or 10 ppm of ethylene (E). In brackets it is indicated whether the clone is a singleton or the cluster it belongs to. Hybridization with the C. sinensis 26 S rDNA is shown in the bottom panel. Normalization of hybridization signals was carried out with respect to the hybridization signal of the C. sinensis rDNA. Values below the panels show the relative quantification of the corresponding hybridization signal referred to the value of the sample E. Those hybridization signals lower than two fold the background intensity were not assessed (-).Click here for file


Co-circulation of multiple dengue virus serotypes has been reported from many parts of the world including India, however concurrent infection with more than one serotype of dengue viruses in the same individual is rarely documented. An outbreak of dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS) occurred in and around Delhi in 2006. This is the first report from India with high percentage of concurrent infections with different dengue virus serotypes circulating during one outbreak.Acute phase sera from patients were tested for the presence of dengue virus RNA by RT-PCR assay. Of the 69 samples tested for dengue virus RNA, 48 (69.5%) were found to be positive. All the four dengue virus serotypes were found to be co-circulating in this outbreak with DENV-3 being the predominant serotype. In addition in 9 of 48 (19%) dengue virus positive samples, concurrent infection with more than one dengue virus serotype were identified.This is the first report in which concurrent infections with different dengue virus serotypes is being reported during an outbreak from India. Delhi is now truly hyperendemic for dengue. Flavivirus, family Flaviviridae) are mosquito borne and the principal vector (Aedes aegypti) is a day-biting domestic mosquito of public importance that breeds in natural or artificial water  in 20 (41.6%), hemorrhagic manifestations and rash in 6 each (12.5%). As per classification based on WHO definition (28), DF was seen in 21 cases with single serotype infection and in 3 cases with concurrent infections, whereas DHF was present in 14 cases with single serotype infection and 6 with concurrent infections. Clinical data was inadequate in 4 cases to reach any conclusion about the severity of illness.By far, to the best of our knowledge, this is the first report on the prevalence of concurrent infections by different dengue virus serotype combinations from an outbreak in India.With the changes in the global epidemiology of dengue during the last 50 years , not onlThe first case of concurrent infections with 2 dengue virus serotypes was reported from Puerto Rico in 1982 , since tIt has been postulated that concurrent infections by multiple dengue virus serotypes may influence the clinical expression of the disease. This is considered as a single major factor for the emergence of DHF .During the dengue outbreaks of 1967, 1970 and 1982 in Delhi, no culture-confirmed cases of DHF/DSS were reported ,13,15,16The seasonal trend of dengue virus infection is reflected by the peak of positive cases observed during post monsoon season i.e. September–October which is in concordance with previous outbreaks ,20. The The most challenging problem associated with patient management in dengue infection is rapid diagnosis. Although the commercially available MAC ELISAs offer improvements over other conventional assays for the diagnosis, however they do not offer serotype specific diagnosis. Diagnosis based on detection of IgM antibodies can only be achieved after 5–7 days of illness. In recent years serological assay based on NS1 antigen detection have become commercially available which claim to provide early diagnosis of dengue within first day of illness. However, these tests are expensive to be used in developing countries. Moreover, a number of these newly developed kits yet need to be validated for dengue virus detection in clinical settings. The detection of concurrent infections can be made by virus isolation in tissue culture followed by indirect immunofluorscence (IFA) using serotype specific monoclonal antibodies and/or RT-PCR -33. HoweIt is now notably clear that the epidemics caused by multiple dengue virus serotypes, have become more frequent on a global basis in the past 18 years . GeneralThe detection of dengue virus RNA by RT-PCR showed that DENV-3 was the most common etiologic agent followed by DENV-1 in this outbreak. All the four dengue virus serotypes were found to co-circulate in the current outbreak of 2006; DENV-3 remained the predominant serotype as reported in 2003–2004 .Previously from Delhi and its surrounding areas, only two concurrent dengue cases were identified  but now This study reveals that DENV-3 has dominated this outbreak even though all four serotypes were found to be co-circulating as detected by RT-PCR. The increasing trend of co-circulation of dengue virus serotypes suggests that Delhi is becoming a hyperendemic state from an endemic one. Although the sample size in this study was small, the study highlights a high percentage of concurrent infections by different dengue virus serotypes for the first time from India.The author(s) declare that they have no competing interests.PB carried out all the RT-PCR experiments, analyzed them and drafted the manuscript. HSC carried out RNA extraction, helped in careful collection of case history and drafted the manuscript. AP and KD were responsible for collection and storage of clinical samples and carried out the clinical sample processing. RG and SK clinically diagnosed the patients and directed the patients to the Virology diagnostic laboratory. SB and LD conceived the study and all the research was carried out in the Virology diagnostic laboratory under SB supervision. All authors read and approved the final manuscript.


In 2007, an outbreak of epizootic hemorrhagic disease (EHD) occurred in Turkey. On the basis of clinical investigation, 41 cattle were suspected to have EHD. Reverse transcription–PCR and sequence analyses indicated that the virus belonged to EHD virus serotype 6, thus confirming EHD virus infection of cattle in Turkey. Orbivirus, family Reoviridae, and is closely related to bluetongue virus (BTV). EHD often causes death in white-tailed deer and, less frequently, a bluetongue-like illness in cattle (Epizootic hemorrhagic disease virus (EHDV) is a member of the genus Culicoides spp. act as vectors, transmitting EHDV between susceptible ruminant hosts . Samples were obtained in tubes with and without EDTA. Complete blood analysis showed that 5 of the cattle with EHD had low leukocyte counts . After uCulicoides variipennis larvae cell line (KC cells) is usually required  to the World Organisation for Animal Health reference laboratory for BTV  for virologic and serologic analysis. All samples were tested for BTV by real-time RT-PCR and for EHDV by conventional RT-PCR . These 6 samples and the 1 original positive cell culture were further tested by serotype-specific RT-PCRs that targeted segment 2 for identification of EHDV serotype. This analysis identified all viruses as EHDV-6, sharing 95.7% nucleotide sequence identity  with the EHDV reference strain 318.Of the selected samples submitted for BTV and EHDV testing, the positive identification of EHDV RNA supports initial clinical identification of an EHD outbreak in Turkey. The negative results from the blood samples may have resulted from degradation of viral RNA during transfer to the laboratory or insufficient sensitivity in the conventional RT-PCR. The propagation of another 6 virus isolates (TUR2007/01–06) by passage through KC cells indicates that virus was indeed present in the original blood samples, although not detected by conventional RT-PCR.That only 1 of the 4 original serum samples was positive for EHDV antibodies by ELISA can be explained by time of sample collection. Antibodies to BTV can be detected from 8 days after infection (This study confirms EHDV infection of cattle in Turkey. EHD needs to be considered in the differential diagnosis of cattle with clinical signs that include fever; stomatitis; lameness; salivation; redness and scaling of the nose and lips; swelling of the tongue; and erosions of the pulvinus dentalis, palatinum, and nose. More detailed studies of EHDV infection in cattle are needed.Hematologic findings in cattle tested for epizootic hemorrhagic disease, Turkey, 2007*


To the Editor: The picornaviruses constitute a large, diverse family of positive-sense RNA viruses, which comprise 8 genera: Enterovirus, Aphthovirus, Cardiovirus, Hepatovirus, Parechovirus, Erbovirus, Kobuvirus, and Teschovirus  to characterize calicivirus in porcine fecal specimens with a primer pair of p289/VN3T20 designed for a 3-kb fragment of the virus, we observed an unexpected band on agarose gel electrophoresis (www.dnastar.com) and were compared with other sequences in GenBank by using BLAST (www.ncbi.nlm.nih.gov/blast/Blast.cgi).To further characterize the virus, we designed primers corresponding to the viral protein (VP) 0 region of kobuvirus on the basis of conserved sequences deduced by comparing the sequences of bovine kobuvirus (GenBank accession no. NC_004421) and Aichi virus (GenBank accession no. NC_001918). An 823-bp fragment was examined and then submitted, together with the 1185-bp sequence, to GenBank under accession no. FJ493623. The obtained sequences were analyzed by using the DNASTAR software package . The phylogenetic analysis showed a single genetic lineage for the novel virus, close to Kobuvirus but phylogenetically distinct from both bovine kobuvirus and Aichi virus, which suggests that the porcine fecal specimen contained a candidate novel species of Kobuvirus (Partial sequences of the 3D region have been used to deduce phylogenetic and taxonomic relationships among picornaviruses; these sequences have been particularly useful for placing viruses within species or genera or for comparing viruses of different genera or families (obuvirus .The filtered fecal samples positive for the virus were inoculated onto RD cells. After 3 serial passages, no obvious cytopathic effect in RD cells was noted. The cells and supernatants in every passage were collected separately for RNA extraction. We then used semiquantitative RT-PCR with glyceraldehyde-3-phosphate dehydrogenase as an internal reference to detect the virus and determine the amount of the viral RNA in the medium. Cells and supernatants of the 3 passages were virus positive, and the control inoculated with phosphate-buffered saline was virus negative. However, with each passage, the amount of viral RNA in the medium decreased. Whether the positive result was caused by residual viruses of the initial inoculation or by the decreased propagation of the virus in the cells is not clear. Further studies, such as continuous serial passages and neutralization assay, are needed to determine the final activity of the virus in RD cells, as well as in other cells such as Vero and HeLa, because several species of picornaviruses have been identified as causing persistent infections in these cells in vitro (Kobuvirus as a causative agent of disease in pigs and a potential zoonotic agent.In conclusion, we report the genetic characterization and biological properties of a new agent in China. Of note, while we were preparing this article, a similar article from Hungary was published (


Susceptibility to infection, duration of illness, and concentration of asymptomatic viral shedding vary between species of swans and geese. The role of wild birds in the epidemiology of the Asian lineage highly pathogenic avian influenza (HPAI) virus subtype H5N1 epizootic and their contribution to the spread of the responsible viruses in Eurasia and Africa are unclear. To better understand the potential role of swans and geese in the epidemiology of this virus, we infected 4 species of swans and 2 species of geese with an HPAI virus of Asian lineage recovered from a whooper swan in Mongolia in 2005, A/whooper swan/Mongolia/244/2005 (H5N1). The highest mortality rates were observed in swans, and species-related differences in clinical illness and viral shedding were evident. These results suggest that the potential for HPAI (H5N1) viral shedding and the movement of infected birds may be species-dependent and can help explain observed deaths associated with HPAI (H5N1) infection in anseriforms in Eurasia. Anser indicus) at Qinghai Lake, People’s Republic of China (Cygnus olor), whooper swans (C. cygnus), tufted ducks (Aythya fuligula), and Canada geese (Branta canadensis) (The first indication of wild bird involvement in the Asian lineage highly pathogenic avian influenza (HPAI) virus (H5N1) epizootic occurred late in 2002 and 2003, when HPAI (H5N1) was isolated from captive and wild birds in Hong Kong Special Administrative Region, People’s Republic of China (Although the ability of Asian lineage HPAI (H5N1) to infect and cause death in wild birds has been documented, the epidemiology of this virus in free-ranging avian populations is unclear. Wild avian species infected by this virus in Asia have been taxonomically diverse, whereas in Europe, most deaths and HPAI virus (H5N1) isolations have been limited to only a few species of geese and swans. A growing body of genetic and epidemiologic evidence suggests that, in 2005, migratory waterfowl played a role in the geographic spread of Asian lineage HPAI virus (H5N1) to Europe  and to then predict the ability of each species to spread the virus into new areas. Susceptibility was determined on the basis of prevalence and onset of illness and death and distribution of microscopic lesions and viral antigen. Viral shedding patterns were based on duration, route, and concentration of viral excretion. We evaluated the potential ability of a given species to geographically move the virus on the basis of the duration and viral titers associated with asymptomatic shedding.C. atratus), trumpeter swan (C. buccinator), mute swan, bar-headed goose, and cackling goose (B. hutchinsii). All birds used in this study were bred in captivity and purchased from commercial breeders in the United States. The swans were 5–6 weeks of age at the time of the experiment. This age was chosen on the basis of availability of birds and size restrictions imposed by the isolation units. Geese were ≈12 weeks of age at the time of the experiment, which corresponds to the age of juvenile waterfowl during the peak prevalence of avian influenza virus (AIV) in wild waterfowl in North America  per 0.1 mL (single-bird inoculum) as determined by standard procedures (A stock of the A/whooper swan/Mongolia/244/2005 (H5N1) (Mongolia/2005) HPAI virus was produced by second passage in 9-day-old embryonated chicken eggs. Allantoic fluid from the inoculated eggs was diluted in brain–heart infusion (BHI) medium to yield a final titer of 10Preinoculation serum was collected from each bird to confirm that they were serologically negative to influenza A type–specific antigens by the agar gel precipitin (AGP) test and the H5 hemagglutinin subtype by the hemagglutinin–inhibition (HI) test. In addition, oropharyngeal and cloacal swabs were collected from each bird to ensure that they were not actively infected and shedding AIV at the start of the study. Two (whooper swan and cackling goose) or 3  birds from each species were inoculated intranasally (IN) with 0.1 mL of the Mongolia/2005 virus solution. After 24 hours, 2 additional birds from each species were placed in the housing unit with the inoculated birds. All birds were monitored daily for illness or death for 14 days. Illness was defined as any clinical abnormality detectable upon physical examination after inoculation with, or contact exposure to, the HPAI virus (H5N1), including weakness, cloudy eyes, respiratory difficulty, shivering, crowding, ruffled feathers, hemorrhage on the unfeathered skin, and neurologic signs, such as tremors, seizures, severe incoordination, and torticollis. Oropharyngeal and cloacal swabs were collected and then placed in BHI with antimicrobial agents  from all birds at 1, 2, 3, 4, 5, 7, 10, and 14 days postexposure (dpe). At 14 dpe, blood was collected from the surviving birds for serologic testing, and the birds were euthanized with intravenous sodium pentobarbital (100 mg/kg body weight). Blood was not collected from birds that died during the course of the study. Necropsies were performed on all birds, and routine tissues were collected for histopathologic and immunohistochemical evaluation. In addition, oropharyngeal and cloacal swabs were collected from all birds that died and were stored in BHI with antimicrobial agents for virus isolation. In reporting the temporal data, 0 days postcontact (when the contact birds were placed into the cage with the inoculated birds) was assumed to be equivalent to 0 days postinoculation.One bird from each species was inoculated IN with a sham solution and housed in a separate unit from the virus-exposed birds. Oropharyngeal and cloacal swabs and preinoculation serum samples were collected from these birds before inoculation to confirm that they were not actively infected with an AIV and were negative for serum antibodies to the type-specific A antigen and the H5 hemagglutinin. These birds were monitored for illness and death for the 14-day trial. At 14 DPE, serum was collected from each sham-inoculated bird for serologic testing, and the birds were euthanized as described above. A necropsy was performed on each bird, and samples were collected for histopathologic and immunohistochemical evaluation.Tissues samples collected at necropsy were preserved in 10% neutral buffered formalin. After fixation, the tissues were routinely processed and embedded in paraffin. Sections were cut at 5 μm and stained with hematoxylin and eosin. Duplicate sections were cut and immunohistochemically stained by using a mouse-derived monoclonal antibody (P13C11) specific for type A influenza virus nucleoprotein antigen as the primary antibody (SEPRL). The procedures used to perform the immunohistochemical testing have been previously described . Challenge virus was detected in oropharyngeal and cloacal swabs from every IN-inoculated and contact bird of each species studied except 1 bar-headed goose, which is described later. Viral shedding was detected in each of the contact swans by 1 dpe but was delayed in contact geese; virus was not detected until 3 dpe in the cackling geese and 2 dpe in the bar-headed geese. Similarly, there was no difference between the onset of detectable clinical signs and death in swans that were inoculated with virus and those that were exposed through contact. Contact geese, however, had a delayed onset of detectable clinical signs  and death  compared with IN-inoculated geese Disease, deaths, viral distribution, and pathology differed among the swans and geese infected with the Mongolia/2005 virus strain . Among aA). Microscopic examination showed that all black swans that died had widespread multiorgan necrosis with mild acute inflammation, which was strongly correlated with the distribution of the virus. All of the black swans shed virus before death and, as with all birds in this study, titers were higher in respiratory secretions than in feces , astrocytes, and other parenchymal cells of the brain and most of the examined visceral organs, as opposed to the vasculotropic distribution in black swans. Microscopic lesions were strongly associated with the anatomic location of detectable viral antigen and consisted of multifocal to coalescing necrosis with mild to moderate heterophilic inflammation. Within this category, the Mongolia/2005 virus infection in mute swans was unique. Clinical signs occurred later (5–7 dpe) in mute swans than in any of the other species examined in this study. The duration of disease in mute swans was extremely short (<24 hours) and comparable to the duration of disease in black swans. The clinical signs observed in mute swans were similar to those in the whooper and trumpeter swans. Birds in all 3 of these species shed high concentrations of virus in respiratory secretions with maximum titers approximating those of the black swans.Susceptibility was similar in the remaining 3 species of swans. Disease and death occurred later in these species, and the duration of illness, with 1 exception, was longer. Clinical signs consisted of mild to moderate listlessness, which progressively worsened to severe listlessness with neurologic signs similar to those observed with the black swans. Viral antigen was detected in the neurons , panel B3.9 EID50/mL) than the 3 geese that died , but the duration of shedding was approximately similar in both oropharyngeal and cloacal swabs.The 2 species of geese differed in their susceptibility to the Mongolia/2005 virus and both were less susceptible than the swan species. All of the cackling geese became sick after inoculation with the Mongolia/2005 virus, but only 3 of the 4 birds died and the remaining bird slowly recovered until clinical signs of disease were no longer apparent. The cackling geese that died exhibited severe listlessness and marked neurologic signs similar to those observed in the swans. The single goose that survived became moderately listless with ruffled feathers and cloudy eyes before clinical signs resolved but did not exhibit neurologic clinical signs during the study. This goose produced postexposure antibodies to AIV that were detected by the AGP and HI tests. Cackling geese that died had a short duration of illness (average duration 1.67 days) as opposed to the goose that survived, which exhibited detectable clinical signs for 9 days before resolution. Viral antigen in the 3 geese that died was restricted to the brain, pancreas, liver, and adrenal gland. Microscopic lesions primarily involved these organs and included multiple foci of necrosis with moderate heterophilic to lymphoplasmocytic inflammation. The single goose that survived had minimal amounts of viral antigen in the neurons of the brain and mild perivascular encephalitis. The surviving goose also shed lower concentrations of virus  than for the geese that died (average duration 2.50 days). All 3 of these surviving geese produced antibodies to AIV that were detected by the AGP and HI tests. Viral antigen and microscopic lesions in bar-headed geese were primarily present in the brain. Viral antigen staining was more widespread in the 2 geese that died than in the 3 that survived. Microscopic lesions consisted of moderate perivascular encephalitis and neuronal necrosis in geese that died and mild perivascular encephalitis in birds that survived. The concentration and duration of viral shedding were similar between bar-headed geese that died and those that survived. Cloacal shedding was detected in all of the bar-headed geese except one, which was one of the surviving birds.During the outbreaks of HPAI (H5N1) of Asian lineage in Europe in 2005–2006, certain duck and swan species were overrepresented in the mortality reports . Some geBlack swans were the most susceptible species to HPAI virus (H5N1) infection, with illness, deaths, and viral distribution similar to results for gallinaceous poultry  birds in these species more time to spread virus during their movements. This is particularly true for mute swans, which shed moderate to high concentrations of virus for several days without showing clinical signs of disease. The longer duration of asymptomatic viral shedding would allow this species ample time to travel and have contact with other wild birds and shared aquatic habitats. Mute swans do not migrate; however, freezing temperatures may cause many populations to move during the winter season as waterways freeze. This possibility has been suggested as a factor that contributed to the spread of HPAI virus (H5N1) in Europe during 2005–2006  infection occurs in ducks up to 4 weeks of age but not in chickens (The cackling geese were more susceptible to HPAI virus (H5N1) than the bar-headed geese, as evidenced by higher proportion of deaths and more systemic viral distribution, and both of these geese species were generally less susceptible than swans. The delayed viral shedding, illness, and deaths of contact geese compared with inoculated geese provide further support that geese are less susceptible than swans. These factors may also suggest that viral transmission would occur at a slower rate within populations of these geese species than in swans. While susceptibility varied between these 2 species, both had similar onsets of disease and death, duration and concentrations of viral shedding, and duration of asymptomatic shedding. On the basis of these parameters, bar-headed geese and cackling geese would be equally efficient disseminators of HPAI virus (H5N1). Cackling geese are closely related to Canada geese, which were affected in some European outbreaks of HPAI virus (H5N1)  among wild species of waterfowl. Several important characteristics of HPAI virus (H5N1) infection differ between waterfowl species, including duration of asymptomatic shedding and duration and concentration of viral shedding. According to these characteristics, mute swans, cackling geese, and bar-headed geese may be recognized as species that pose a greater risk for transmission and spread of HPAI (H5N1). Relatively few wild avian species, rather than anseriform species as a whole, may have contributed to most of the spread of HPAI (H5N1) within Eurasia. This conclusion is consistent with observed mortality patterns during outbreaks and from the failure to detect HPAI (H5N1) in clinically normal anseriform species despite intensive sampling. This finding implies that the epidemiology of this particular lineage of AIV in waterfowl populations differs from that of low-pathogenicity AIV that naturally circulate in wild birds and that the establishment of a silent (without detectable disease and death) natural reservoir for Asian lineage HPAI virus (H5N1) strains within wild waterfowl populations may be unlikely.


In chickens, as in most birds, female gonad morphogenesis is asymmetrical. Gonads appear first rather similarly, but only the left one undergoes full differentiation and gives rise to a functional ovary. The right gonad, in which the cortex does not develop, remains restricted to the medulla and finally regresses. Opportunity was taken of this left-right asymmetry to perform a suppression subtractive hybridization screening to select for transcripts preferentially expressed in the developing left ovary as compared to the right one, and thus identify genes that are potentially involved in the process of ovarian differentiation.Ovex1 according to its expression profile, corresponds to an endogenous retrovirus that has not been previously characterized. It is transcribed as full-length and singly spliced mRNAs and contains three uninterrupted open reading frames coding potentially for proteins with homology to Gag and Pro-Pol retroviral polyproteins and a third protein showing only a weak similarity with Env glycoproteins. Ovex1 is severely degenerated; it is devoid of typical long terminal repeats and displays some evidence of recombination. An orthologous Ovex1 locus was identified in the genome of zebra finch, a member of a different bird order, and similar sequences were detected in turkey, guinea fowl, and duck DNA. The relationship between these sequences follows the bird phylogeny, suggesting vertical transmission of the endogenous retrovirus for more than 100 million years.One of these transcripts, named Ovex1 is transcribed in chicken gonads with a sex-dependent and left-right asymmetrical pattern. It is first expressed in the cortex of the left indifferent gonads of both sexes. Expression is transient in the left testis and absent in the right one. In developing ovaries, Ovex1 transcription increases sharply in the left cortex and is weakly detected in the medulla. After folliculogenesis, Ovex1-expressing cells constitute the follicular granulosa cell layer. Ovex1 expression highlights a striking desquamation process that leads to profound cortical remodeling associated with follicle morphogenesis.Evidence for a selection pressure at the protein level suggests that this endogenous retrovirus, expressed in the ovarian supporting cell lineage, might play an active role in bird ovarian physiology. In chickens, as in most birds, gonad differentiation is characterized by left-right (L/R) asymmetry. In the female, only the left gonad becomes a functional ovary. The right one fails to fully differentiate and ultimately disappears. By contrast, both male gonads, initially asymmetrical, become functional testes. Bird sex determination is not fully understood. The heterogametic sex, with a ZW karyotype, is female and the homogametic sex, with two Z chromosomes, is male. Unlike in mammals, the initial genetic sex trigger is not clearly identified .th day of incubation (E4), with identification of the genital ridge, a thickening of the coelomic epithelium on the medial aspect of the mesonephros, in which primordial germ cells, migrating from the germinal crescent, are going to settle  (locus LOC422926), located on the chromosome 4 long arm . It revealed a 99.7% identity with the 3'-untranslated region (UTR) of a hypothetical gene [GenBank:arm Fig. . This geXM_430004], coding for a hypothetical protein of unknown nature  corresponding to this locus have an ovarian origin. Some of them extend 5' from the locus Fig. , suggesture Fig.  and exteure Fig. .+1 or A+4  using, in a first experiment, Ov6849a as antisense primer Fig. . Two seqA+4 Fig. , a few bA+4 Fig. .The mRNA polyadenylation site was identified by 3' RACE Fig. , using aOvex1 contains one AAUAAA and three AUUAAA hexamers followed by U and GU-rich elements, clustered in the region of nucleotides 6082 to 6669, which might constitute polyadenylation signals leading to premature transcription arrest. However, the efficiency of these signals in vivo is low as demonstrated by the RT-PCR amplification of cDNA fragments D, E, and F  revealed the presence of a sequence with 83% identity to chicken Ovex1 . The sequence is incomplete, due to the presence of a sequencing gap of some 600 bp in this first version of the genome. This Ovex1 homolog is located on zebra finch chromosome 4, syntenic to chicken chromosome 4 long arm, between the CD8 and SMYD1 loci as for chicken Ovex1. Such conservation indicates that this sequence is the ortholog of chicken Ovex1. The sequence of zebra finch Ovex1 is given in additional file Ovex1 sequence). Conservation of the TATA box, the polyadenylation signal, and of sequences surrounding the donor and acceptor splice sites suggests that zebra finch Ovex1 is transcribed and spliced as chicken Ovex1.Blat search in the recently sequenced genome of a passerine bird Ovex1 sequence appear to be present as a single copy in chicken  and zebra finch (taeGut1) genomes. In contrast, in both species the last third of Ovex1 contains sequences identified by RepeatMasker as the internal part of a multi-copy LTR-containing element, GGLTR11-int  that corresponds to Ovex1 has been found to be expressed at a rate 6-time lower in hen ovaries of a chicken strain selected for its high egg production, compared with another strain with low egg production  and [GenBank:FJ406462]. Partial Gag sequences of turkey, guinea fowl and duck are respectively  and partial RT sequences .Complete nucleotide sequences of the chicken NC_001408]; cENS3, Pol-like protein ENS-3, [GenBank:NP_989963]; Dev1, Dendrobates ventrimaculatus ERV 1, [EMBL:X95795]; EAV-HP, Avian endogenous retrovirus EAV-HP, [EMBL:AJ292966]; FFV, Feline foamy virus, [GenBank:NP_056914]; GGERV-LC, ERV3 endogenous retrovirus from chicken, RepBase [AJ289709]; HERV-L, Human endogenous retroviral element HERV-L, [EMBL:X89211]; HFV, Human foamy virus, [GenBank:NC_001736]; HIV1, Human immunodeficiency virus 1, [GenBank:NC_001802]; HTLV1, Human T-lymphotropic virus 1, [GenBank:NC_001436]; MMLV, Moloney murine leukemia virus (Pol polyprotein), [Swiss-Prot:P03355]; MMLV, Moloney murine leukemia virus (Env polyprotein), [Swiss-Prot:P03385]; MMTV, Mouse mammary tumor virus, [GenBank:NC_001503]; MuERV-L, Mus musculus endogenous retroviral sequence MuERV-L, [EMBL:Y12713]; PERV, Porcine endogenous retrovirus, [EMBL:AJ279057]; REV-A, Reticuloendotheliosis virus isolate REV-A, [GenBank:DQ237900]; RV_Tinamou, RV-Tinamou partial mRNA for polyprotein, [EMBL:AJ225235]; SnRV, Snakehead retrovirus, [GenBank:NC_001724]; SpeV, Sphenodon endogenous retroviral gene for protease and reverse transcriptase, [EMBL:X85037]; TERV, Tetraonine endogenous retrovirus, [GenBank:AF289082]; WDSV, Walleye dermal sarcoma virus, [GenBank:NC_001867]; WEHV1, Walleye epidermal hyperplasia virus type 1, [GenBank:AF133051]; WEHV2, Walleye epidermal hyperplasia virus type 2, [GenBank:AF133052]; Xen1, Xenopus laevis endogenous retrovirus Xen1, [EMBL:AJ506107]; ZFERV, Danio rerio endogenous retrovirus ZFERV, [GenBank:AF503912].Abbreviations and database accession numbers of other sequences referred to in the text and figures are as follows: ALV, Avian leukosis virus,  (nucleotides 1 to 330), [GenBank:XM_416179] (nt 121 to 825) and [EMBL:X03805] (nt 827 to1752). For Ovex1, a Pol probe corresponding to nucleotides 2511 to 3245 was used in the experiments reported. Hybridization of a 3'-UTR probe (nt 8633 to 8919) gave similar results. Hybridization with sense probes was negative. Apoptotic cells were detected by the TUNEL method, using In Situ Cell Death Detection Kit, Fluorescein (Roche), on frozen sections previously treated for in situ hybridization. After PBS washing, sections were incubated for 1 hour at room temperature with the TUNEL Label Mixture containing terminal transferase.eviously , using aescribed . Other pWhite Leghorn eggs, were treated on day 4 of incubation (HH stage 24) with a single injection of 1 mg fadrozole (CGS 16949A), a specific nonsteroidal aromatase inhibitor , as described . EmbryosThe authors declare that they have no competing interests.In situ hybridization studies were designed by SM and DCE, carried out by SM and NC and analyzed by SM who participated in drafting the manuscript. All authors read and approved the final manuscriptDCE conceived the study, carried out the SSH selection and molecular biology studies, and drafted the manuscript. Figure S2. Effect of the internal polyadenylation signals.Click here for fileFigure S3. Partial zebra finch Ovex1 sequence.Click here for fileFigure S4. Alignment of chicken and zebra finch Ovex1 5'-proximal DNA sequences.Click here for fileFigure S5. Alignment of Ovex1 putative proteins.Click here for fileFigure S6. Structure and conservation of ORF3-encoded proteins.Click here for fileOvex1 sequencesTable S7 – Polymorphisms in chicken . Polymorphisms observed in the Ovex1 sequence between the Red Jungle Fowl  and the white Leghorn chicken strain (this study).Click here for fileFigure S8. Alignment of Ovex1 RT and homologous sequences.Click here for fileFigure S9. Detection of apoptotic cells in chicken ovary at hatching.Click here for fileTable S1. Primers and PCR conditions.Click here for file


To assess the total medical costs and productivity losses associated with the 1993 waterborne outbreak of cryptosporidiosis in Milwaukee, Wisconsin, including the average cost per person with mild, moderate, and severe illness, we conducted a retrospective cost-of-illness analysis using data from 11 hospitals in the greater Milwaukee area and epidemiologic data collected during the outbreak. The total cost of outbreak-associated illness was $96.2 million: $31.7 million in medical costs and $64.6 million in productivity losses. The average total costs for persons with mild, moderate, and severe illness were $116, $475, and $7,808, respectively. The potentially high cost of waterborne disease outbreaks should be considered in economic decisions regarding the safety of public drinking water supplies. Cryptosporidium parvum, a protozoan parasite that causes gastrointestinal illness, is transmitted by ingestion of oocysts excreted in human or animal feces. Typical modes of transmission include person to person, animal to person, by exposure to contaminated surfaces, and by ingestion of impure food or water  when persons were still likely to seek medical care , intangible costs associated with pain and suffering, or the cost to the local, state, and federal government to investigate and control the outbreak.We used several parameters to estimate the direct medical costs associated with diarrheal illness during the Milwaukee cryptosporidiosis outbreak .Cryptosporidium and other intestinal pathogens. For the two samples, we included all costs for the inpatient admission or emergency department visit, regardless of whether the cost was directly attributable to cryptosporidiosis. Charts were excluded when the hospital admission was primarily for another condition  and when the onset of gastrointestinal illness occurred after hospital admission.To assess the usage and average cost of inpatient admissions  and outpatient services associated with emergency department visits, we reviewed all hospital medical charts for persons with laboratory-confirmed cryptosporidiosis as identified by the hospitals’ laboratory records. Because the sensitivity of diagnostic testing is relatively low, and many persons were not tested during the outbreak, we also reviewed a sample of charts for persons admitted to the emergency department or hospital with diarrhea for at least 2 days, as identified by the following diagnostic codes from the International Classification of Diseases, 9th Revision, Clinical Modification (CD-9-CM) listed in one of the first four diagnosis categories on the hospital discharge record: 007.20, 008.80, 009 and subcategories, 079.90, 234.10, 276 and subcategories, 558.90, and 999 and subcategories. During these admissions, either no laboratory testing was performed or tests were negative for From the medical records, we collected data on resource use during hospitalization or emergency department visit, the use of ambulance transportation, self-reported use of medication before an emergency department visit or inpatient admission, and physician-prescribed medication following an emergency department visit or inpatient admission. Charges for hospitalization included diagnostic, laboratory, hospital room, and technical services ; attending physician and nursing staff; medication; emergency department services; and other supplies or services not identified in the previous categories .Charges for emergency department visits and hospitalizations were converted to costs by using an average cost-to-charge ratio of 0.67, based on ratios obtained from 6 of the 11 hospitals sampled in the greater Milwaukee area; this figure is comparable to Wisconsin’s average operating cost-to-charge ratio (0.70) reported for urban hospitals in 1993 (We assumed that 95% of persons with moderate illness sought the care of a physician (one visit only) and that the remaining 5% required an emergency department visit. . For the latter group, we assumed that no additional physician visits were needed before or after the emergency department visit. The proportion of persons with severe illness who had a physician visit before hospitalization was obtained from chart review. We assumed that one physician visit was needed before (and none after) the hospitalization. The cost of a physician visit ($45) was obtained from data collected by the City of Milwaukee Health Department.  This figure is in the range found by other studies that have estimated the cost of a physician visit as ranging from $40 (1992 dollars) to $53 (1994 U.S. dollars) during this period  for the cost of an ambulance transport, and we assumed that the average distance per transport was 5 miles  for medications prescribed upon discharge for persons with moderate and severe illness. We assumed that medications prescribed for persons with moderate illness seeking an emergency department visit also applied to persons with moderate illness seeking physician care. Retail drug prices in 1993 were used to calculate all costs  and 223 persons who met our case definition for severe illness . Seventeen percent of persons with moderate illness and 63% of persons with severe illness in our sample had laboratory-confirmed cryptosporidiosis.Average costs of illness for persons with mild, moderate, and severe illness were $116 for mild, $475 for moderate, and $7,808 for severe . Direct The total cost of illness associated with the cryptosporidiosis outbreak in Milwaukee was approximately $96.2 million: $31.7 million in direct medical costs and $64.6 million in productivity losses . MedicalThe average cost for an emergency department visit for persons with moderate illness was $224 . For perThe massive waterborne outbreak of cryptosporidiosis in 1993 in Milwaukee caused illness in approximately 403,000 persons and generated substantial healthcare costs and productivity losses. We estimate that on average, ill persons incurred approximately $79 in medical costs and $160 in productivity losses, resulting in total medical costs of $31.7 million in total medical costs and $64.6 million in total lost productivity. Since epidemiologic estimates of incidence contribute substantially to total cost estimates for any outbreak, information on average cost of illness by severity can be applied to any range of epidemiologic estimates to assess the sensitivity of total costs. For example, in the Milwaukee outbreak, the 95% confidence interval for burden  of illness ranged from 370,000 to 435,000 persons  , the Environmental Protection Agency, the Wisconsin Division of Health , the City of Milwaukee Health Department, the Milwaukee Water Works, and 17 local health departments, were estimated at >$2 million immediately following the outbreak . A class action suit filed by the residents of Milwaukee against the city continued to generate costs for the local government well beyond the immediate outbreak period. Businesses similarly experienced financial hardship during the outbreak because of employee illness, the necessity of using bottled water during the city’s boil-water advisory, and a decrease in beverage and food sales overall. Unaccounted costs for the infected person include costs incurred for self-protection  and the pain and suffering associated with illness.Although the $96.2 million in illness costs attributed to the Milwaukee outbreak is substantial, estimated monetized annual costs of waterborne disease in the United States have been estimated at $21.9 billion (1991 dollars) (1 is a reminder that failure to maintain safe drinking water supplies has substantial impact on the health and economy of a community.In an era of limited health resources, decision makers must choose how to allocate resources to improve the public’s health. Measures taken to reduce the risk of waterborne cryptosporidiosis will also prevent other waterborne diseases. Water authorities often face the predicament of dealing with decreasing raw water quality, the high costs of new technologies, water filtration systems that do not completely remove all potentially pathogenic organisms, and increased public demand for safe water. The cost of this outbreak, which can be balanced against the cost of measures for preventing future outbreaks,


Non-parametric linkage methods have had limited success in detecting gene by gene interactions. Using affected sibling-pair (ASP) data from all replicates of the simulated data from Problem 3, we assessed the statistical power of three approaches to identify the gene × gene interaction between two loci on different chromosomes. The first method conditioned on linkage at the primary disease susceptibility locus (DR), to find linkage to a simulated effect modifier at Locus A with a mean allele sharing test. The second approach used a regression-based mean test to identify either the presence of interaction between the two loci or linkage to the A locus in the presence of linkage to DR. The third method applied a conditional logistic model designed to test for the presence of interacting loci. The first approach had decreased power over an unconditional linkage analysis, supporting the idea that gene × gene interaction cannot be detected with ASP data. The regression-based mean test and the conditional logistic model had the lowest power to detect gene × gene interaction, possibly because of the complex recoding of the tri-allelic DR locus for use as a covariate. We conclude that the ASP approaches tested have low power to successfully identify the interaction between the DR and A loci despite the large sample size, which may be due to the low prevalence of the high-risk DR genotypes. Additionally, the lack of data on discordant sibships may have decreased the power to identify gene × gene interactions. Linkage analysis methods to identify gene × gene interactions in complex diseases have been developed -4, howevFirst, we examined a mean test variant of the conditional methodology presented by Cox et al. . The motWe also examined the power and type I error of two other covariate based approaches to detect epistasis with varying covariate coding schemes of the genotyped locus (DR). The first is a regression-based mean test that can be used to test for the presence of gene × environment interactions in ASPs . By treaThe simulated data set from GAW15 Problem 3 consists of a 5-cM microsatellite genome scan for each of 100 replicates, in which each replicate represents a random sample of 1500 ASPs with RA and their parents (four-person pedigrees). Data from all replicates were analyzed with researchers unblinded to the simulation parameters. The DR locus on chromosome 6 was simulated as the primary disease susceptibility locus with additional genetic and environmental factors affecting the risk of disease. Only Locus A on chromosome 16 was simulated as an effect modifier on the risk of RA due to the DR locus. Thus, it was used as the test locus for gene × gene interaction. The DR locus has three alleles: X, 1, and 4, with prevalences 0.65, 0.1, and 0.25, respectively. The A locus is diallelic and acts in a dominant fashion with a prevalence of 0.3 for risk allele "A". Assuming Hardy-Weinberg proportions at the DR locus and holding other risk factors constant, the marginal risk of RA due to the DR locus in individuals with the A allele at locus A is 5.2, which decreases to 3.5 in individuals who are homozygous for the low-risk "a" allele at Locus A.Multipoint allele sharing from ASPs was determined using GENIBD (S.A.G.E. v5.2). Parental genotype data were recoded to missing for deceased individuals. Various coding schemes for the covariate DR locus were examined including: 1) the X allele under an additive genetic model; 2) the 4 allele under an additive model; and, 3) a linear combination of the covariates based entirely on the simulated risk levels provided in the solutions. The "linear" coding for each individual given their DR locus genotype was constructed as follows: 1) "X/X" genotype was assigned a value of 0; 2) "X/1" or "X/4" genotypes were assigned a value of 1; 3) "4/4" genotype was assigned a value of 2 and, 4) "1/4" or "1/1" genotypes were assigned a value of 3. This coding scheme was designed to capture in a simple fashion the increased risk associated with the DR1 and DR4 alleles, on the basis of the values of the risk multipliers which are 0.8, 1, 2, and 6, respectively.p-value for linkage on chromosome 16 was less than 0.05 was used to estimate power. Type I error was determined by taking the chromosomes with no simulated disease or quantitative trait loci and averaging the number of times a replicate exceeded the threshold value of the test statistic at the α = 0.05 level. Within each replicate, the locus with the highest proportion of alleles shared IBD within a 20-cM region of the DR locus was selected as representing the point with most significant evidence for linkage to the DR locus because linkage can be detected as far as 20 cM away from the causal locus [The percent of replicates in which the al locus .π be the mean proportion of alleles shared IBD between ASPs at a marker locus. The mean test compares the average amount of allele sharing IBD at a marker locus to the expected value of π = 0.5. Any excess of allele sharing across all sibling pairs is believed to be due to a disease susceptibility locus. A traditional t-statistic can be computed to compare the observed allele sharing to the null value of 0.5 with n - 1 degrees of freedom. A genome scan using the mean test was repeated, selecting only ASPs in which the proportion of alleles shared IBD was greater than or equal to a cut-off value, thus extracting families with evidence for linkage to the DR locus. Three cut-off values were selected: 0.5, 0.7, and 0.9. By testing various subsets, we were effectively applying 0,1 weights proposed by Cox et al. [Let π0) regression model is equivalent to the mean test, where εi represent the errors for each ASP i that are normally distributed with mean 0 and variance σ2: πi = π0 + εi [π0 - 0.5)/(s.e.(π0)))2. The regression-based mean test is extended to allow for the inclusion of a mean centered covariate Xi that captures the joint values of the sibling pairs at the DR locus as described above [Alternatively, an intercept only  with the constraint that λ2 = 3.634λ1 - 2.634 [λ1 = exp(β + γx), where β measures the genetic effect at the marker and x is the sib-pair covariate. The DR locus was included as a covariate by summing each sibling pair's individual values using the aforementioned genotype codes that were mean-corrected. A likelihood ratio test was conducted by comparing 2ln10 times the difference in LOD scores between models with and without the covariate to a LODPAL (S.A.G.E. v 5.2) implements the conditional logistic model , which eα = 0.05 level using all ASPs in each replicate. Restricting the sample sizes in each replicate by selecting ASPs with the proportion of alleles shared IBD at the DR locus greater than or equal to 0.5 resulted in slightly decreased power to detect linkage at the A locus than the complete data set (24%). DR allele sharing cutoffs of 0.7 or 0.9 did not increase power to detect linkage . The type I error of these tests averaged, 10%, 9%, 9%, and 13% for cutpoints of 0.5, 0.7, 0.9, and the complete data set, respectively. To examine heterogeneity, we restricted the sample to those sib pairs with allele sharing less than 0.3 and 0.1, and the power again barely exceeded the type I error rate (data not shown).The conditional method using the subsetting approach did not provide additional power to detect linkage above and beyond using the entire data set to detect a main linkage effect of Locus A. Figure β coefficient. Figure Similarly, the mean interaction test had limited power to detect evidence for linkage to the A locus or evidence for a significant interaction using a test of the The conditional logistic methodology did not detect the interaction at the A locus, with the power ranging from 1 to 9% in the 40-cM region around the A locus. This power never exceeded the type I error. Even coding the covariates in a manner that mimicked the actual simulated risk parameters through a linear coding scheme did not improve the power to detect linkage.α = 0.05 to detect linkage to the A locus in the presence of linkage to DR. There was no difference between the conditional method, which used a restricted sample, and the mean test and conditional logistic models, demonstrating that this lack of power was not due to insufficient sample size. Our results were quite similar to those of Brock et al. [π > 0.5) was greatest, followed by the joint test of π and β, and that the interaction only model had no less than 10% power. The power to detect interaction only is generally much lower than the power to detect linkage when allowing for interaction [None of the methods we examined had enough power at a type I error rate of k et al. , who anak et al. . Using Gk et al. , we founeraction , so our eraction  suggestseraction . UltimatOur analyses of the GAW15 data also illustrate the challenges of testing for gene × gene interaction for complex diseases. First, we found that our analysis was hampered by the complexity of the simulated model. While the interaction was simulated to be large for certain genotypes, the prevalence of those genotypes was low. For example, the largest simulated multiplicative interaction between DR and the "A" allele of locus A was the DR4/DR4 genotype; however, the prevalence of DR4/DR4 was approximately 0.1. Gauderman and Siegmund demonstrate that, assuming a prevalence of exposure is at least 0.5, the increased risk must be greater than 3 to have sufficient power to detect gene × "environment" interaction . In our In summary, we observed that the most commonly used current methods for detecting gene × gene interaction in ASP data had low power to detect the interaction between DR and A in the simulated data set. This lack of power is likely due to the lack of information in ASP data compared to having discordant pair data and/or the low prevalence of the high-risk DR genotypes and the complex nature of the simulated risk multipliers. Although complicated, this simulated data probably more accurately depicts real complex disease data; thus, we believe further research on linkage methods that can more powerfully detect epistasis while minimizing type I error is warranted.The author(s) declare that they have no competing interests.