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A new method for intrinsic terminator prediction based on Rnall, an RNA local secondary structure prediction algorithm developed recently, and two U-tail score schemas are developed. By optimizing three parameters (thermodynamic energy of RNA hairpin structure, U-tail T weight, and U-tail hybridization energy), the method can recognize 92.25% of known terminators while rejecting 98.48% of predicted RNA local secondary structures in coding regions (negative control) as false intrinsic terminators in E. coli. This method was applied to scan the genome of Synechococcus sp. WH8102, and we predicted 266 intrinsic terminators, which included 232 protein-coding genes, 12 tRNA genes, and 3 rRNA genes. About 17% of these terminators are located at the end of operons. It is also identified 8 pairs of bio-directional terminators. The method for intrinsic terminator prediction has been incorporated into Rnall, which is available at http://digbio.missouri.edu/∼wanx/Rnall/.

The availability of the complete genome sequence for Shewanella oneidensis MR-1 has permitted a comprehensive characterization of the ferric uptake regulator (Fur) modulon in this dissimilatory metal-reducing bacterium. We have employed targeted gene mutagenesis, DNA microarrays, proteomic analysis using liquid chromatography-mass spectrometry, and computational motif discovery tools to define the S. oneidensis Fur regulon. Using this integrated approach, we identified nine probable operons (containing 24 genes) and 15 individual open reading frames (ORFs), either with unknown functions or encoding products annotated as transport or binding proteins, that are predicted to be direct targets of Fur-mediated repression. This study suggested, for the first time, possible roles for four operons and eight ORFs with unknown functions in iron metabolism or iron transport-related functions. Proteomic analysis clearly identified a number of transporters, binding proteins, and receptors related to iron uptake that were up-regulated in response to a fur deletion and verified the expression of nine genes originally annotated as pseudogenes. Comparison of the transcriptome and proteome data revealed strong correlation for genes shown to be undergoing large changes at the transcript level. A number of genes encoding components of the electron transport system were also differentially expressed in a fur deletion mutant. The gene omcA (SO1779), which encodes a decaheme cytochrome c , exhibited significant decreases in both mRNA and protein abundance in the fur mutant and possessed a strong candidate Fur-binding site in its upstream region, thus suggesting that omcA may be a direct target of Fur activation.

To effectively monitor biodegrading populations, a comprehensive 50-mer-based oligonucleotide microarray was developed based on most of the 2,402 known genes and pathways involved in biodegradation and metal resistance. This array contained 1,662 unique and group-specific probes with 7 cells in the presence of background RNA. Strong linear relationships between the signal intensity and the target DNA and RNA were observed ( r 2 = 0.95 to 0.99). Application of this type of microarray to analyze naphthalene-amended enrichment and soil microcosms demonstrated that microflora changed differently depending on the incubation conditions. While the naphthalene-degrading genes from Rhodococcus -type microorganisms were dominant in naphthalene-degrading enrichments, the genes involved in naphthalene (and polyaromatic hydrocarbon and nitrotoluene) degradation from gram-negative microorganisms, such as Ralstonia , Comamonas , and Burkholderia , were most abundant in the soil microcosms. In contrast to general conceptions, naphthalene-degrading genes from Pseudomonas were not detected, although Pseudomonas is widely known as a model microorganism for studying naphthalene degradation. The real-time PCR analysis with four representative genes showed that the microarray-based quantification was very consistent with real-time PCR ( r 2 = 0.74). In addition, application of the arrays to both polyaromatic-hydrocarbon- and benzene-toluene-ethylbenzene-xylene-contaminated and uncontaminated soils indicated that the developed microarrays appeared to be useful for profiling differences in microbial community structures. Our results indicate that this technology has potential as a specific, sensitive, and quantitative tool in revealing a comprehensive picture of the compositions of biodegradation genes and the microbial community in contaminated environments, although more work is needed to improve detection sensitivity.

An interactive clustering model based on positional weight matrices is described and results obtained using the model to analyze gene regulation patterns in archaea are presented. The 5' flanking sequences of ORFs identified in four archaea, Sulfolobus solfataricus, Pyrobaculum aerophilum, Halobacterium sp. NRC-1, and Pyrococcus abyssi, were clustered using the model. Three regular patterns of clusters were identified for most ORFs. One showed genes with only a ribosome-binding site; another showed genes with a transcriptional regulatory region located at a constant location with respect to the start codon. A third pattern combined the previous two. Both P. aerophilum and Halobacterium sp. NRC-1 exhibited clusters of genes that lacked any regular pattern. Halobacterium sp. NRC-1 also presented regular features not seen in the other organisms. This group of archaea seems to use a combination of eubacterial and eukaryotic regulatory features as well as some unique to individual species. Our results suggest that interactive clustering may be used to examine the divergence of the gene regulatory machinery in archaea and to identify the presence of archaea-specific gene regulation patterns.

Aminopeptidases (APN) may play a role in host colonization of M. gallinarum. Characterization of endogenous APN activity suggests that the leucine APN (LAP) of M. gallinarum is a metallo-aminopeptidase activated by Mn2+ and is present in the cytosol and possibly associated with the inner leaflet of the membrane. A 1.36-kb open reading frame (ORF) identified from overlapping genomic phage clones showed 68% nucleotide identity and 51% amino acid identity with the M. salivarium LAP gene. This ORF is expressed as a 1.5-kb monocistronic transcript and is present as a single copy in M. gallinarum. This gene sequence was modified to account for codon usage, and expression in E. coli produced a 51-kDa protein, which compares well with the product predicted from the ORF. This ORF is a strong candidate for contributing the LAP activity of M. gallinarum protein extracts.

Mycoplasma Gallinarum is a commensal with a host range that includes most poultry. This property of M. gallinarum may reflect unique mechanisms for colonization and persistence in various hosts. In previous studies a leucine aminopeptidase (LAP) gene candidate was cloned from a M. gallinarum recombinant genomic library and characterized. Here we evaluate the LAP gene from M. gallinarum at the protein level. A recombinant fusion protein was purified and employed as an antigen to immunize chickens to obtain polyclonal anti-LAP serum. The antiserum was utilized to identify the subcellular location by immuoblotting with Triton X-114 partitions of M. gallinarum proteins. Our results of these experiments show that the LAP gene product is located in the cytoplasmic fraction of the M. gallinarum cell.

Our long term goal is to determine the role that pMGA hemagglutinins play in Mycoplasma gallisepticum F-strain (termed as F-strain for brevity) persistence in poultry. To do this however, we first had to identify the pMGA genes expressed by an isolate of the F-strain. To identify F-strain pMGA genes, a genomic library was constructed in bacteriophage lambda and screened with polyclonal antisera raised against F-strain surface antigens capable of inhibiting agglutination of chicke n red blood cells. One phage clone was identified, designated λ 9, which remained positive through additional rounds of screening and was sequenced. Sequence data analysis predicted one complete and two partial open reading frames (ORF) arranged in tandem within the 4.5 kb genomic insert, termed ORF 9.1, ORF 9.2 and ORF 9.3, which showed significant homology to the pMGA gene family of M. gallisepticum . The number of GAA trinucleotide repeats in the intergenic region of 9.3 ORF suggested that this ORF is expressed. The pMGA cDNAs amplified from the F-strain showed significant homology to the 9.3 ORF. One set of cDNAs however, differed from the 9.3 ORF sequence by a repeat of the sequence "AACCAAA" in the 5' end. We conclude that the F-strain vaccine isolate expresses pMGA gene variants, similar to what has been described in field strains of M. gallisepticum.

Domestic poultry act as a reservoir for persistent H5N1 endemicity in Vietnam, and the circulation of poultry flocks across farms and to market is thought to drive the spatial movement and evolution of avian influenza viruses. Using a dataset of complete or nearly full genomic sequences from highly pathogenic H5N1 avian influenza viruses collected in domestic poultry in Vietnam from 2003 to 2007, we explore potential differences in genetic characteristics according to species of isolation and the spatio-temporal characteristics of the viruses. Clustering algorithms and analysis of variance indicate that H5N1 viruses in Vietnam show differences in the amount of genetic change that chicken viruses experience as compared to duck viruses, with duck viruses showing higher rates of molecular evolution on all eight of influenza's gene segments. There also exist distinct patterns of genetic differentiation according to the year in which they were isolated. These findings suggest that genetic evolution of avian influenza viruses is continuous through time but could also be mediated by the species in which the viruses occur, information which has implications for prevention efforts.

In the spring of 2012 an outbreak of H7N3 highly pathogenic (HP) avian influenza virus (AIV) occurred in poultry in Mexico. Vaccination was implemented as a control measure, along with increased biosecurity and surveillance. At that time there was no commercially available H7 AIV vaccine in North America; therefore, a recent H7N3 wild bird isolate of low pathogenicity from Mexico (A/cinnamon teal/Mexico/2817/2006 H7N3) was selected and utilized as the vaccine seed strain. In these studies, the potency and efficacy of this vaccine strain was evaluated in chickens against challenge with the 2012 Jalisco H7N3 HPAIV. Although vaccine doses of 256 and 102 hemagglutinating units (HAU) per bird decreased morbidity and mortality significantly compared to sham vaccinates, a dose of 512 HAU per bird was required to prevent mortality and morbidity completely. Additionally, the efficacy of 11 other H7 AIV vaccines and an antigenic map of hemagglutination inhibition assay data with all the vaccines and challenge viruses were evaluated, both to identify other potential vaccine strains and to characterize the relationship between genetic and antigenic distance with protection against this HPAIV. Several other isolates provided adequate protection against the 2012 Jalisco H7N3 lineage, but antigenic and genetic differences were not clear indicators of protection because the immunogenicity of the vaccine seed strain was also a critical factor.

Vaccination is the primary strategy for the prevention and control of influenza outbreaks. However, the manufacture of influenza vaccine requires a high-yield seed strain, and the conventional methods for generating such strains are time consuming. In this study, we developed a novel method to rapidly generate high-yield candidate vaccine strains by integrating error-prone PCR, site-directed mutagenesis strategies, and reverse genetics. We used this method to generate seed strains for the influenza A(H1N1)pdm09 virus and produced six high-yield candidate strains. We used a mouse model to assess the efficacy of two of the six candidate strains as a vaccine seed virus: both strains provided complete protection in mice against lethal challenge, thus validating our method. Results confirmed that the efficacy of these candidate vaccine seed strains was not affected by the yield-optimization procedure.

Rapid identification of influenza antigenic variants will be critical in selecting optimal vaccine candidates and thus a key to developing an effective vaccination program. Recent studies suggest that multiple simultaneous mutations at antigenic sites accumulatively enhance antigenic drift of influenza A viruses. However, pre-existing methods on antigenic variant identification are based on analyses from individual sites. Because the impacts of these co-evolved sites on influenza antigenicity may not be additive, it will be critical to quantify the impact of not only those single mutations but also multiple simultaneous mutations or co-evolved sites. Here, we developed and applied a computational method, AntigenCO, to identify and quantify both single and co-evolutionary sites driving the historical antigenic drifts. AntigenCO achieved an accuracy of up to 90.05% for antigenic variant prediction, significantly outperforming methods based on single sites. AntigenCO can be useful in antigenic variant identification in influenza surveillance.

Outbreaks of low-pathogenicity avian influenza (LPAI) viruses of the H7N3 subtype were first detected in Italy in October 2002, and the virus continued to circulate between 2002 and 2004 in a densely populated poultry area in the northeast portion of that country. This virus circulated in unvaccinated and vaccinated poultry farms, and the infection was controlled in August 2003 by culling, control of movements, improved biosecurity, and heterologous vaccination. In 2004, H7N3 reoccurred in vaccinated poultry farms in which infection had been successfully controlled by the vaccination program. To shed light on this occurrence and the temporal pattern and genetic basis of antigenic drift for avian influenza viruses (AIVs) in the absence and presence of heterologous vaccination, a collection of H7N3 viruses isolated in 2002 and 2004 were characterized genetically and antigenically. Molecular analysis showed that viruses isolated in the 2004 outbreaks after the implementation of vaccination had acquired specific amino acid signatures, most of which were located at reported antibody binding sites of the hemagglutinin (HA) protein. Antigenic characterization of these 2004 isolates showed that they were antigenically different from those isolated prior to the implementation of vaccination. This is the first report on antigenic and genetic evolution of H7 LPAI viruses following the application of heterologous vaccination in poultry. These findings may have an impact on control strategies to combat AI infections in poultry based on vaccination.

An avian-like H3N2 influenza A virus (IAV) has recently caused sporadic canine influenza outbreaks in China and Korea, but the molecular mechanisms involved in the interspecies transmission of H3N2 IAV from avian to canine species are not well understood. Sequence analysis showed that residue 222 in haemagglutinin (HA) is predominantly tryptophan (W) in the closely related avian H3N2 IAV, but was leucine (L) in canine H3N2 IAV. In this study, reassortant viruses rH3N2-222L (canine-like) and rH3N2-222W (avian-like) with HA mutation L222W were generated using reverse genetics to evaluate the significance of the L222W mutation on receptor binding and host tropism of H3N2 IAV. Compared with rH3N2-222W, rH3N2-222L grew more rapidly in MDCK cells and had significantly higher infectivity in primary canine tracheal epithelial cells. Tissue-binding assays demonstrated that rH3N2-222L had a preference for canine tracheal tissues rather avian tracheal tissues, whereas rH3N2-222W favoured slightly avian rather canine tracheal tissues. Glycan microarray analysis suggested both rH3N2-222L and rH3N2-222W bound preferentially to α2,3-linked sialic acids. However, the rH3N2-222W had more than twofold less binding affinity than rH3N2-222L to a set of glycans with Neu5Aca2–3Galb1–4(Fuca-)-like or Neu5Aca2–3Galb1–3(Fuca-)-like structures. These data suggest the W to L mutation at position 222 of the HA could facilitate infection of H3N2 IAV in dogs, possibly by increasing the binding affinities of the HA to specific receptors with Neu5Aca2–3Galb1–4(Fuca-) or Neu5Aca2–3Galb1–3(Fuca-)-like structures that are present in dogs.

Background Phylogenetic networks are employed to visualize evolutionary relationships among a group of nucleotide sequences, genes or species when reticulate events like hybridization, recombination, reassortant and horizontal gene transfer are believed to be involved. In comparison to traditional distance-based methods, quartet-based methods consider more information in the reconstruction process and thus have the potential to be more accurate. Results We introduce QuartetSuite, which includes a set of new quartet-based methods, namely QuartetS, QuartetA, and QuartetM, to reconstruct phylogenetic networks from nucleotide sequences. We tested their performances and compared them with other popular methods on two simulated nucleotide sequence data sets: one generated from a tree topology and the other from a complicated evolutionary history containing three reticulate events. We further validated these methods to two real data sets: a bacterial data set consisting of seven concatenated genes of 36 bacterial species and an influenza data set related to recently emerging H7N9 low pathogenic avian influenza viruses in China. Conclusion QuartetS, QuartetA, and QuartetM have the potential to accurately reconstruct evolutionary scenarios from simple branching trees to complicated networks containing many reticulate events. These methods could provide insights into the understanding of complicated biological evolutionary processes such as bacterial taxonomy and reassortant of influenza viruses.

The advances in high throughput omics technologies have made it possible to characterize molecular interactions within and across various species. Alignments and comparison of molecular networks across species will help detect orthologs and conserved functional modules and provide insights on the evolutionary relationships of the compared species. However, such analyses are not trivial due to the complexity of network and high computational cost. Here we develop a mixture of global and local algorithm, BinAligner, for network alignments. Based on the hypotheses that the similarity between two vertices across networks would be context dependent and that the information from the edges and the structures of subnetworks can be more informative than vertices alone, two scoring schema, 1-neighborhood subnetwork and graphlet, were introduced to derive the scoring matrices between networks, besides the commonly used scoring scheme from vertices. Then the alignment problem is formulated as an assignment problem, which is solved by the combinatorial optimization algorithm, such as the Hungarian method. The proposed algorithm was applied and validated in aligning the protein-protein interaction network of Kaposi's sarcoma associated herpesvirus (KSHV) and that of varicella zoster virus (VZV). Interestingly, we identified several putative functional orthologous proteins with similar functions but very low sequence similarity between the two viruses. For example, KSHV open reading frame 56 (ORF56) and VZV ORF55 are helicase-primase subunits with sequence identity 14.6%, and KSHV ORF75 and VZV ORF44 are tegument proteins with sequence identity 15.3%. These functional pairs can not be identified if one restricts the alignment into orthologous protein pairs. In addition, BinAligner identified a conserved pathway between two viruses, which consists of 7 orthologous protein pairs and these proteins are connected by conserved links. This pathway might be crucial for virus packing and infection.

The efficacy of current influenza vaccines requires a close antigenic match between circulating and vaccine strains. As such, timely identification of emerging influenza virus antigenic variants is central to the success of influenza vaccination programs. Empirical methods to determine influenza virus antigenic properties are time-consuming and mid-throughput and require live viruses. Here, we present a novel, experimentally validated, computational method for determining influenza virus antigenicity on the basis of hemagglutinin (HA) sequence. This method integrates a bootstrapped ridge regression with antigenic mapping to quantify antigenic distances by using influenza HA1 sequences. Our method was applied to H3N2 seasonal influenza viruses and identified the 13 previously recognized H3N2 antigenic clusters and the antigenic drift event of 2009 that led to a change of the H3N2 vaccine strain., IMPORTANCE This report supplies a novel method for quantifying antigenic distance and identifying antigenic variants using sequences alone. This method will be useful in influenza vaccine strain selection by significantly reducing the human labor efforts for serological characterization and will increase the likelihood of correct influenza vaccine candidate selection.

The demonstrated link between the emergence of H3N2 variant (H3N2v) influenza A viruses (IAVs) and swine exposure at agricultural fairs has raised concerns about the human health risk posed by IAV-infected swine. Understanding the antigenic profiles of IAVs circulating in pigs at agricultural fairs is critical to developing effective prevention and control strategies. Here, 68 H3N2 IAV isolates recovered from pigs at Ohio fairs (2009 to 2011) were antigenically characterized. These isolates were compared with other H3 IAVs recovered from commercial swine, wild birds, and canines, along with human seasonal and variant H3N2 IAVs. Antigenic cartography demonstrated that H3N2 IAV isolates from Ohio fairs could be divided into two antigenic groups: (i) the 2009 fair isolates and (ii) the 2010 and 2011 fair isolates. These same two antigenic clusters have also been observed in commercial swine populations in recent years. Human H3N2v isolates from 2010 and 2011 are antigenically clustered with swine-origin IAVs from the same time period. The isolates recovered from pigs at fairs did not cross-react with ferret antisera produced against the human seasonal H3N2 IAVs circulating during the past decade, raising the question of the degree of immunity that the human population has to swine-origin H3N2 IAVs. Our results demonstrate that H3N2 IAVs infecting pigs at fairs and H3N2v isolates were antigenically similar to the IAVs circulating in commercial swine, demonstrating that exhibition swine can function as a bridge between commercial swine and the human population.

Mycoplasma hyopneumoniae (M. hyopneumoniae) causes a chronic respiratory disease with high morbidity and low mortality in swine, and has been presented as a major cause of growth retardation in the swine industry. Aerosol vaccination presents a needle free, high throughput, and efficient platform for vaccine delivery, and has been widely applied in poultry vaccination. However, aerosol vaccines have rarely been used in swine vaccination primarily because the long and curving respiratory track of swine presents a barrier for vaccine particle delivery. To develop an effective M. hyopneumoniae aerosol vaccine, three major barriers need to be overcome: to optimize particle size for aerosol delivery, to maintain the viability of mycoplasma cells in the vaccine, and to optimize the environmental conditions for vaccine delivery. In this study, an aerosol mycoplasma vaccine was successfully developed based on a conventional live attenuated M. hyopneumoniae vaccine. Specifically, the Pari LCD nebulizer was used to produce an aerosol vaccine particle size less than 5 μm; and a buffer with 5% glycerol was developed and optimized to prevent inactivation of M. hyopneumoniae caused by aerosolization and evaporation. Before nebulization, the room temperature and relative humidity were control to 20-25 °C and 70-75%, respectively, which helped maintain the viability of aerosol vaccine. Animal experiments demonstrated that this newly developed aerosol vaccine was effectively delivered to swine low respiratory track, being confirmed by nested-PCR, in situ hybridization and scanning electron microscope. Moreover, M. hyopneumoniae specific sIgA secretion was detected in the nasal swab samples at 14 days post-immunization. To our knowledge, this is the first report on a live M. hyopneumoniae aerosol vaccine.

Phylogenetic networks can model reticulate evolutionary events such as hybridization, recombination, and horizontal gene transfer. However, reconstructing such networks is not trivial. Popular character-based methods are computationally inefficient, whereas distance-based methods cannot guarantee reconstruction accuracy because pairwise genetic distances only reflect partial information about a reticulate phylogeny. To balance accuracy and computational efficiency, here we introduce a quartet-based method to construct a phylogenetic network from a multiple sequence alignment. Unlike distances that only reflect the relationship between a pair of taxa, quartets contain information on the relationships among four taxa; these quartets provide adequate capacity to infer a more accurate phylogenetic network. In applications to simulated and biological data sets, we demonstrate that this novel method is robust and effective in reconstructing reticulate evolutionary events and it has the potential to infer more accurate phylogenetic distances than other conventional phylogenetic network construction methods such as Neighbor-Joining, Neighbor-Net, and Split Decomposition. This method can be used in constructing phylogenetic networks from simple evolutionary events involving a few reticulate events to complex evolutionary histories involving a large number of reticulate events. A software called "Quartet-Net" is implemented and available at http://sysbio.cvm.msstate.edu/QuartetNet/.

In China, approximately 20% of the animal original influenza A viruses have molecular markers of amantadine resistance. Through phylogenetic data analyses and geospatial statistical analyses, this study suggests emergence of amantadine resistance in animal influenza could be due to selection pressures in China, for example, amantadine usage in some areas.

The H1N1 subtype of influenza A virus has caused two of the four documented pandemics and is responsible for seasonal epidemic outbreaks, presenting a continuous threat to public health. Co-circulating antigenically divergent influenza strains significantly complicates vaccine development and use. Here, by combining evolutionary, structural, functional, and population information about the H1N1 proteome, we seek to answer two questions: (1) do residues on the protein surfaces evolve faster than the protein core residues consistently across all proteins that constitute the influenza proteome? and (2) in spite of the rapid evolution of surface residues in influenza proteins, are there any protein regions on the protein surface that do not evolve? To answer these questions, we first built phylogenetically-aware models of the patterns of surface and interior substitutions. Employing these models, we found a single coherent pattern of faster evolution on the protein surfaces that characterizes all influenza proteins. The pattern is consistent with the events of inter-species reassortment, the worldwide introduction of the flu vaccine in the early 80’s, as well as the differences caused by the geographic origins of the virus. Next, we developed an automated computational pipeline to comprehensively detect regions of the protein surface residues that were 100% conserved over multiple years and in multiple host species. We identified conserved regions on the surface of 10 influenza proteins spread across all avian, swine, and human strains; with the exception of a small group of isolated strains that affected the conservation of three proteins. Surprisingly, these regions were also unaffected by genetic variation in the pandemic 2009 H1N1 viral population data obtained from deep sequencing experiments. Finally, the conserved regions were intrinsically related to the intra-viral macromolecular interaction interfaces. Our study may provide further insights towards the identification of novel protein targets for influenza antivirals.

Background A striking characteristic of the past four influenza pandemic outbreaks in the United States has been the multiple waves of infections. However, the mechanisms responsible for the multiple waves of influenza or other acute infectious diseases are uncertain. Understanding these mechanisms could provide knowledge for health authorities to develop and implement prevention and control strategies. Materials and Methods We exhibit five distinct mechanisms, each of which can generate two waves of infections for an acute infectious disease. The first two mechanisms capture changes in virus transmissibility and behavioral changes. The third mechanism involves population heterogeneity (e.g., demography, geography), where each wave spreads through one sub-population. The fourth mechanism is virus mutation which causes delayed susceptibility of individuals. The fifth mechanism is waning immunity. Each mechanism is incorporated into separate mathematical models, and outbreaks are then simulated. We use the models to examine the effects of the initial number of infected individuals (e.g., border control at the beginning of the outbreak) and the timing of and amount of available vaccinations. Results Four models, individually or in any combination, reproduce the two waves of the 2009 H1N1 pandemic in the United States, both qualitatively and quantitatively. One model reproduces the two waves only qualitatively. All models indicate that significantly reducing or delaying the initial numbers of infected individuals would have little impact on the attack rate. Instead, this reduction or delay results in a single wave as opposed to two waves. Furthermore, four of these models also indicate that a vaccination program started earlier than October 2009 (when the H1N1 vaccine was initially distributed) could have eliminated the second wave of infection, while more vaccine available starting in October would not have eliminated the second wave.

Locating areas where genetic change is inhibited can illuminate underlying processes that drive evolution of pathogens. The persistence of highly pathogenic H5N1 avian influenza in Vietnam since 2003, and the continuous molecular evolution of Vietnamese avian influenza viruses, indicates that local environmental factors are supportive not only of incidence but also of viral adaptation. This article explores whether gene flow is constant across Vietnam, or whether there exist boundary areas where gene flow exhibits discontinuity. Using a dataset of 125 highly pathogenic H5N1 avian influenza viruses, principal components analysis and wombling analysis are used to indicate the location, magnitude, and statistical significance of genetic boundaries. Results show that a small number of geographically minor boundaries to gene flow in highly pathogenic H5N1 avian influenza viruses exist in Vietnam, but that overall there is little division in genetic exchange. This suggests that differences in genetic characteristics of viruses from one region to another are not the result of barriers to H5N1 viral exchange in Vietnam, and that H5N1 avian influenza is able to spread relatively unimpeded across the country.

International audience; Since the isolation of A/goose/Guangdong/1/1996 (H5N1) in farmed geese in southern China, highly pathogenic H5N1 avian influenza viruses have posed a continuous threat to both public and animal health. The non-synonymous mutation of the H5 hemagglutinin (HA) gene has resulted in antigenic drift, leading to difficulties in both clinical diagnosis and vaccine strain selection. Characterizing H5N1's antigenic profiles would help resolve these problems. In this study, a novel sparse learning method was developed to identify antigenicity-associated sites in influenza A viruses on the basis of immunologic data sets (i.e., from hemagglutination inhibition and microneutralization assays) and HA protein sequences. Twenty-one potential antigenicity-associated sites were identified. A total of 17 H5N1 mutants were used to validate the effects of 11 of these predicted sites on H5N1's antigenicity, including 7 newly identified sites not located in reported antibody binding sites. The experimental data confirmed that mutations of these tested sites lead to changes in viral antigenicity, validating our method.

This study identifies population and environment drivers of genetic change in H5N1 avian influenza viruses (AIV) in Vietnam using a landscape genetics approach. While prior work has examined how combinations of local-level environmental variables influence H5N1 occurrence, this research expands the analysis to the complex genetic characteristics of H5N1 viruses. A dataset of 125 highly pathogenic H5N1 AIV isolated in Vietnam from 2003 to 2007 is used to explore which population and environment variables are correlated with increased genetic change among viruses. Results from non-parametric multidimensional scaling and regression analyses indicate that variables relating to both the environmental and social ecology of humans and birds in Vietnam interact to affect the genetic character of viruses. These findings suggest that it is a combination of suitable environments for species mixing, the presence of high numbers of potential hosts, and in particular the temporal characteristics of viral occurrence, that drive genetic change among H5N1 AIV in Vietnam.

Advances in glycan array technology have provided opportunities to automatically and systematically characterize the binding specificities of glycan-binding proteins. However, there is still a lack of robust methods for such analyses. In this study, we developed a novel quantitative structure-activity relationship (QSAR) method to analyze glycan array data. We first decomposed glycan chains into mono-, di-, tri- or tetrasaccharide subtrees. The bond information was incorporated into subtrees to help distinguish glycan chain structures. Then, we performed partial least-squares (PLS) regression on glycan array data using the subtrees as features. The application of QSAR to the glycan array data of different glycan-binding proteins demonstrated that PLS regression using subtree features can obtain higher R(2) values and a higher percentage of variance explained in glycan array intensities. Based on the regression coefficients of PLS, we were able to effectively identify subtrees that indicate the binding specificities of a glycan-binding protein. Our approach will facilitate the glycan-binding specificity analysis using the glycan array. A user-friendly web tool of the QSAR method is available at http://bci.clemson.edu/tools/glycan_array.

Human infections of H5N1 highly pathogenic avian influenza virus have continued to occur in China without corresponding outbreaks in poultry, and there is little conclusive evidence of the source of these infections. Seeking to identify the source of the human infections, we sequenced 31 H5N1 viruses isolated from humans in China (2005 to 2010). We found a number of viral genotypes, not all of which have similar known avian virus counterparts. Guided by patient questionnaire data, we also obtained environmental samples from live poultry markets and dwellings frequented by six individuals prior to disease onset (2008 and 2009). H5N1 viruses were isolated from 4 of the 6 live poultry markets sampled. In each case, the genetic sequences of the environmental and corresponding human isolates were highly similar, demonstrating a link between human infection and live poultry markets. Therefore, infection control measures in live poultry markets are likely to reduce human H5N1 infection in China.

Identification of the genetic origin of influenza A viruses will facilitate understanding of the genomic dynamics, evolutionary pathway, and viral fitness of influenza A viruses. The exponential increases of influenza sequences have expanded the coverage of influenza genetic pool, thus potentially reducing the biases for influenza progenitor identification. However, these large amounts of data generate a great challenge in progenitor identification. To increase computational efficiency, IPMiner is developed by integrating complete composition vector for genetic distance calculation and minimum spanning tree algorithm for progenitor identification. IPMiner is available to at http://sysbio.cvm.msstate.edu/IPMiner.

Influenza antigenic cartography projects influenza antigens into a two or three dimensional map based on immunological datasets, such as hemagglutination inhibition and microneutralization assays. A robust antigenic cartography can facilitate influenza vaccine strain selection since the antigenic map can simplify data interpretation through intuitive antigenic map. However, antigenic cartography construction is not trivial due to the challenging features embedded in the immunological data, such as data incompleteness, high noises, and low reactors. To overcome these challenges, we developed a computational method, temporal Matrix Completion-Multidimensional Scaling (MC-MDS), by adapting the low rank MC concept from the movie recommendation system in Netflix and the MDS method from geographic cartography construction. The application on H3N2 and 2009 pandemic H1N1 influenza A viruses demonstrates that temporal MC-MDS is effective and efficient in constructing influenza antigenic cartography. The web sever is available at http://sysbio.cvm.msstate.edu/AntigenMap.

Background The Shewanella oneidensis MR-1 genome encodes a predicted orphan DNA-binding response regulator, SO2426. Previous studies with a SO2426-deficient MR-1 strain suggested a putative functional role for SO2426 in the regulation of iron acquisition genes, in particular, the siderophore (hydroxamate) biosynthesis operon so3030-3031-3032. To further investigate the functional role of SO2426 in iron homeostasis, we employed computational strategies to identify putative gene targets of SO2426 regulation and biochemical approaches to validate the participation of SO2426 in the control of siderophore biosynthesis in S. oneidensis MR-1. Results In silico prediction analyses revealed a single 14-bp consensus motif consisting of two tandem conserved pentamers (5'-CAAAA-3') in the upstream regulatory regions of 46 genes, which were shown previously to be significantly down-regulated in a so2426 deletion mutant. These genes included so3030 and so3032, members of an annotated siderophore biosynthetic operon in MR-1. Electrophoretic mobility shift assays demonstrated that the SO2426 protein binds to its motif in the operator region of so3030. A "short" form of SO2426, beginning with a methionine at position 11 (M11) of the originally annotated coding sequence for SO2426, was also functional in binding to its consensus motif, confirming previous 5' RACE results that suggested that amino acid M11 is the actual translation start codon for SO2426. Alignment of SO2426 orthologs from all sequenced Shewanella spp. showed a high degree of sequence conservation beginning at M11, in addition to conservation of a putative aspartyl phosphorylation residue and the helix-turn-helix (HTH) DNA-binding domain. Finally, the so2426 deletion mutant was unable to synthesize siderophores at wild-type rates upon exposure to the iron chelator 2,2'-dipyridyl. Conclusions Collectively, these data support the functional characterization of SO2426 as a positive regulator of siderophore-mediated iron acquisition and provide the first insight into a coordinate program of multiple regulatory schemes controlling iron homeostasis in S. oneidensis MR-1.

This study reports four sporadic cases of H3N2 canine influenza in Southern China, which were identified from sick dogs from May 2006 to October 2007. The evolutionary analysis showed that all eight segments of these four viruses are avian-origin and phylogenetically close to the H3N2 canine influenza viruses reported earlier in South Korea. Systematic surveillance is required to monitor the disease and evolutionary behavior of this virus in canine populations in China.

Different from most other host-specific mycoplasmas, Mycoplasma gallinarum has been isolated from various hosts, such as poultry, pig, cattle, and sheep. The wide distribution among different hosts, the low pathogenesis, and the weak host immunological responses suggest this mycoplasma has a unique host adaptation mechanism. In this study, we applied two-dimensional liquid chromatography electrospray ionization tandem mass spectrometry (2D LC–MS/MS) to characterize the protein profiling of M. gallinarum. Our results suggest that M. gallinarum possesses homologs of cytadhesin proteins found in other mycoplasmas lacking an organized tip organelle. Our results showed that there are possibly multiple aminopeptidase gene homologs present in M. gallinarum, which might be involved in nutrient acquisition of M. gallinarum. The information present here would be useful for future studies to identify genes responsible for the colonization and host adaptation properties of M. gallinarum.

Background Characterizing the structural properties of protein interaction networks will help illuminate the organizational and functional relationships among elements in biological systems. Results In this paper, we present a systematic exploration of the core/periphery structures in protein interaction networks (PINs). First, the concepts of cores and peripheries in PINs are defined. Then, computational methods are proposed to identify two types of cores, k-plex cores and star cores, from PINs. Application of these methods to a yeast protein interaction network has identified 110 k-plex cores and 109 star cores. We find that the k-plex cores consist of either "party" proteins, "date" proteins, or both. We also reveal that there are two classes of 1-peripheral proteins: "party" peripheries, which are more likely to be part of protein complex, and "connector" peripheries, which are more likely connected to different proteins or protein complexes. Our results also show that, besides connectivity, other variations in structural properties are related to the variation in biological properties. Furthermore, the negative correlation between evolutionary rate and connectivity are shown toysis. Moreover, the core/periphery structures help to reveal the existence of multiple levels of protein expression dynamics. Conclusion Our results show that both the structure and connectivity can be used to characterize topological properties in protein interaction networks, illuminating the functional organization of cellular systems.

Highly pathogenic avian influenza H5N1 virus was detected in poultry seized at two ports of entry located in Lang Son Province, Vietnam. Sequence analysis of the hemagglutinin (HA) genes from five H5N1 virus isolates and ten PCR amplicons from chicken cloacal samples revealed their close phylogenetic relationship to clade 7 H5N1 HA genes. However, these HA genes exhibited extensive genetic divergence at both the nucleotide and amino acid levels in comparison to previously described clade 7 viruses; e.g., A/chicken/Shanxi/2/2006. In addition, hemagglutination inhibition tests revealed antigenic differences between these and previously isolated H5N1 viruses from Vietnam. These results indicate that viruses with clade 7 HA are evolving rapidly in poultry in Southeast Asia.

Highly pathogenic avian influenza (HPAI) H5N1 viruses have caused dramatic economic losses to the poultry industry of Vietnam and continue to pose a serious threat to public health. As of June 2008, Vietnam had reported nearly one third of worldwide laboratory confirmed human H5N1 infections. To better understand the emergence, spread and evolution of H5N1 in Vietnam we studied over 300 H5N1 avian influenza viruses isolated from Vietnam since their first detection in 2001. Our phylogenetic analyses indicated that six genetically distinct H5N1 viruses were introduced into Vietnam during the past seven years. The H5N1 lineage that evolved following the introduction in 2003 of the A/duck/Hong Kong/821/2002-like viruses, with clade 1 hemagglutinin (HA), continued to predominate in southern Vietnam as of May 2007. A virus with a clade 2.3.4 HA newly introduced into northern Vietnam in 2007, reassorted with pre-existing clade 1 viruses, resulting in the emergence of novel genotypes with neuraminidase (NA) and/or internal gene segments from clade 1 viruses. A total of nine distinct genotypes have been present in Vietnam since 2001, including five that were circulating in 2007. At least four of these genotypes appear to have originated in Vietnam and represent novel H5N1 viruses not reported elsewhere. Geographic and temporal analyses of H5N1 infection dynamics in poultry suggest that the majority of viruses containing new genes were first detected in northern Vietnam and subsequently spread to southern Vietnam after reassorting with pre-existing local viruses in northern Vietnam. Although the routes of entry and spread of H5N1 in Vietnam remain speculative, enhanced poultry import controls and virologic surveillance efforts may help curb the entry and spread of new HPAI viral genes.

A comprehensive gene collection for S. oneidensis was constructed using the lambda recombinase (Gateway) cloning system. A total of 3584 individual ORFs (85%) have been successfully cloned into the entry plasmids. To validate the use of the clone set, three sets of ORFs were examined within three different destination vectors constructed in this study. Success rates for heterologous protein expression of S. oneidensis His- or His/GST- tagged proteins in E. coli were approximately 70%. The ArcA and NarP transcription factor proteins were tested in an in vitro binding assay to demonstrate that functional proteins can be successfully produced using the clone set. Further functional validation of the clone set was obtained from phage display experiments in which a phage encoding thioredoxin was successfully isolated from a pool of 80 different clones after three rounds of biopanning using immobilized anti-thioredoxin antibody as a target. This clone set complements existing genomic (e.g., whole-genome microarray) and other proteomic tools (e.g., mass spectrometry-based proteomic analysis), and facilitates a wide variety of integrated studies, including protein expression, purification, and functional analyses of proteins both in vivo and in vitro.

DNA-DNA hybridization has been established as an important technology in bacterial species taxonomy and phylogenetic analysis. In this study, we analyzed how the efficiency with which the genomic DNA from one species hybridizes to the genomic DNA of another species (DNA-DNA hybridization) in microarray analysis relates to the similarity between two genomes. We found that the predicted DNA-DNA hybridization based on genome sequence similarity correlated well with the experimentally determined microarray hybridization. Between closely related strains, significant numbers of highly divergent genes (55% identity) and/or the accumulation of mismatches between conserved genes lowered the DNA-DNA hybridization signal, and this reduced the hybridization signals to below 70% for even bacterial strains with over 97% 16S rRNA gene identity. In addition, our results also suggest that a DNA-DNA hybridization signal intensity of over 40% indicates that two genomes at least shared 30% conserved genes (60% gene identity). This study may expand our knowledge of DNA-DNA hybridization based on genomic sequence similarity comparison and further provide insights for bacterial phylogeny analyses.

A new method called Complete Composition Vector (CCV), which is a collection of Composition Vectors (CV), is described to infer evolutionary relationships between species using their complete genomic sequences. Such a method bypasses the complexity of performing multiple sequence alignments and avoids the ambiguity of choosing individual genes for species tree construction. It is expected to effectively retain the rich evolutionary information contained in the whole genomic sequence. The method was applied to infer the evolutionary footprints for several datasets that have been previously studied. The final phylogenies were built by an improved clustered Neighbour-Joining method. The generated phylogenetic trees are highly consistent with taxonomy hierarchy and previous studies, with some biologically interesting disagreements.

The influenza A virus is a negative-stranded RNA virus composed of eight segmented RNA molecules, including polymerases (PB2, PB1, PA), hemagglutinin (HA), nucleoprotein (NP), neuraminidase (NA), matrix protein (MP), and nonstructure gene (NS). The influenza A viruses are notorious for rapid mutations, frequent reassortments, and possible recombinations. Among these evolutionary events, reassortments refer to exchanges of discrete RNA segments between co-infected influenza viruses, and they have facilitated the generation of pandemic and epidemic strains. Thus, identification of reassortments will be critical for pandemic and epidemic prevention and control. This paper presents a reassortment identification method based on distance measurement using complete composition vector (CCV) and segment clustering using a minimum spanning tree (MST) algorithm. By applying this method, we identified 34 potential reassortment clusters among 2,641 PB2 segments of influenza A viruses. Among the 83 serotypes tested, at least 56 (67.46%) exchanged their fragments with another serotype of influenza A viruses. These identified reassortments involve 1,957 H2N1 and 1,968 H3N2 influenza pandemic strains as well as H5N1 avian influenza virus isolates, which have generated the potential for a future pandemic threat. More frequent reassortments were found to occur in wild birds, especially migratory birds. This MST clustering program is written in Java and will be available upon request.

Motivation: The availability of the whole genomic sequences of HIV-1 viruses provides an excellent resource for studying the HIV-1 phylogenies using all the genetic materials. However, such huge volumes of data create computational challenges in both memory consumption and CPU usage.Results: We propose the complete composition vector representation for an HIV-1 strain, and a string scoring method to extract the nucleotide composition strings that contain the richest evolutionary information for phylogenetic analysis. In this way, a large-scale whole genome phylogenetic analysis for thousands of strains can be done both efficiently and effectively. By using 42 carefully curated strains as references, we apply our method to subtype 1156 HIV-1 strains (10.5 million nucleotides in total), which include 825 pure subtype strains and 331 recombinants. Our results show that our nucleotide composition string selection scheme is computationally efficient, and is able to define both pure subtypes and recombinant forms for HIV-1 strains using the 5000 top ranked nucleotide strings.Availability: The Java executable and the HIV-1 datasets are accessible through ‘http://www.cs.ualberta.ca/~ghlin/src/WebTools/hiv.phpContact: ghlin@cs.ualberta.caSupplementary information: Supplementary data are available at Bioinformatics online.

The avian influenza virus (AIV) has eight genomic segments (hemagglutinin [HA], neuraminidase [NA], RNA polymerase subunit A [PA], RNA polymerase subunit B1 [PB1], RNA polymerase subunit B2 [PB2], nucleoprotein [NP], nonstructural gene [NS], and matrix protein [M]). The genetic reassortments, recombinations, and mutations lead to a rapid emergence of novel genotypes of the AIVs during their evolution. These emerging viruses provide a large reservoir for pandemic strains. Here we describe a novel computational strategy for genetic reassortment identification. In contrast to the traditional phylogenetic approaches, our method views the genotypes through the modules in networks. Genetic segments with short phylogenetic distance are grouped into modules. Our method is not limited to the number of sequences. We applied this method in reassortment identification of NP segments in H5N1 AIVs. We identified two new potential reassortments for H5N1 AIVs beyond the reported genotypes in literature.

Existing HIV-1 genotyping systems require a computationally expensive phase of multiple sequence alignments and the alignments must have a sufficiently high quality for accurate genotyping. This is particularly a challenge when the number of strains is large. Here we propose a whole genome composition distance (WGCD) to measure the evolutionary closeness between two HIV-1 whole genomic RNA sequences, and use that measure to develop an HIV-1 genotyping system. Such a WGCD-based genotyping system avoids multiple sequence alignments and does not require any pre-knowledge about the evolutionary rates. Experimental results showed that the system is able to correctly identify the known subtypes, sub-subtypes, and individual circulating recombinant forms.

Since the first H7N9 human case in Shanghai, February 19, 2013, the emerging avian-origin H7N9 influenza A virus has become an epizootic virus in China, posing a potential pandemic threat to public health. From April 2 to April 28, 2013, some 422 oral-pharyngeal and cloacal swabs were collected from birds and environmental surfaces at five live poultry markets (LPMs) and 13 backyard poultry farms (BPFs) across three cities, Wuxi, Suzhou, and Nanjing, in the Yangtze Delta region. In total 22 isolates were recovered, and six were subtyped as H7N9, nine as H9N2, four as H7N9/H9N2, and three unsubtyped influenza A viruses. Genomic sequences showed that the HA and NA genes of the H7N9 viruses were similar to those of the H7N9 human isolates, as well as other avian-origin H7N9 isolates in the region, but the PB1, PA, NP, and MP genes of the sequenced viruses were more diverse. Among the four H7N9/H9N2 mixed infections, three were from LPM, whereas the other one was from the ducks at one BPF, which were H7N9 negative in serologic analyses. A survey of the bird trading records of the LPMs and BPFs indicates that trading was a likely route for virus transmission across these regions. Our results suggested that better biosecurity and more effective vaccination should be implemented in backyard farms, in addition to biosecurity management in LPMs.

Peptide compositions constructed out of whole sets of protein sequences can be used as species signatures for phylogenetic analysis. To account for point mutations, an amino acid substitution model is integrated into the complete composition vectors through a novel peptide clustering algorithm. Such a refined signature is expected to highlight deeper evolutionary relationships among the species and employed into the whole genome phylogenetic analysis to define a new evolutionary distance measure. Computational experiments have been set up to validate the effectiveness of this new measure and a vertebrate evolutionary tree using a dataset of 832 proteins for 64 vertebrates is reported.

We derive and validate a novel statistical model for confidence assessment of protein identification results using peptide mass fingerprint data. We simulate the digestion of the proteins and compare each peptide mass with the input mass. We compute scores from this matching of peptide and compute the distribution of scores for all the proteins in the database. Based on the distribution, we can provide the expectation value for a protein match in the database. We conclude that, given the complexity and noise of the data, the best method for effective confidence matching is using one scoring scheme for matching and another scoring scheme for confidence assessment.

Summary: Antigenic cartography is a useful technique to visualize and minimize errors in immunological data by projecting antigens to 2D or 3D cartography. However, a 2D cartography may not be sufficient to capture the antigenic relationship from high-dimensional immunological data. AntigenMap 3D presents an online, interactive, and robust 3D antigenic cartography construction and visualization resource. AntigenMap 3D can be applied to identify antigenic variants and vaccine strain candidates for pathogens with rapid antigenic variations, such as influenza A virus. Availability and implementation: http://sysbio.cvm.msstate.edu/AntigenMap3D Contact: wan@cvm.msstate.edu; wanhenry@yahoo.com

Antigenic characterization based on serological data, such as Hemagglutination Inhibition (HI) assay, is one of the routine procedures for influenza vaccine strain selection. In many cases, it would be impossible to measure all pairwise antigenic correlations between testing antigens and reference antisera in each individual experiment. Thus, we have to combine and integrate the HI tables from a number of individual experiments. Measurements from different experiments may be inconsistent due to different experimental conditions. Consequently we will observe a matrix with missing data and possibly inconsistent measurements. In this paper, we develop a new mathematical model, which we refer to as Joint Matrix Completion and Filtering, for HI data integration. In this approach, we simultaneously handle the incompleteness and uncertainty of observations by assuming that the underlying merged HI data matrix has low rank, as well as carefully modeling different levels of noises in each individual table. An efficient blockwise coordinate descent procedure is developed for optimization. The performance of our approach is validated on synthetic and real influenza datasets. The proposed joint matrix completion and filtering model can be adapted as a general model for biological data integration, targeting data noises and missing values within and across experiments.