Functional significance of the hemadsorption activity of influenza virus neuraminidase and its alteration in pandemic viruses

Human influenza viruses derive their genes from avian viruses. The neuraminidase (NA) of the avian viruses has, in addition to the catalytic site, a separate sialic acid binding site (hemadsorption site) that is not present in human viruses. The biological significance of the NA hemadsorption activity in avian influenza viruses remained elusive. A sequence database analysis revealed that the NAs of the majority of human H2N2 viruses isolated during the influenza pandemic of 1957 differ from their putative avian precursor by amino acid substitutions in the hemadsorption site. We found that the NA of a representative pandemic virus A/Singapore/1/57 (H2N2) lacks hemadsorption activity and that a single reversion to the avian-virus-like sequence (N367S) restores hemadsorption. Using this hemadsorption-positive NA, we generated three NA variants with substitutions S370L, N400S and W403R that have been found in the hemadsorption site of human H2N2 viruses. Each substitution abolished hemadsorption activity. Although, there was no correlation between hemadsorption activity of the NA variants and their enzymatic activity with respect to monovalent substrates, all four hemadsorption-negative NAs desialylated macromolecular substrates significantly slower than did the hemadsorption-positive counterpart. The NA of the 1918 pandemic virus A/Brevig Mission/1/18 (H1N1) also differed from avian N1 NAs by reduced hemadsorption activity and less efficient hydrolysis of macromolecular substrates. Our data indicate that the hemadsorption site serves to enhance the catalytic efficiency of NA and they suggest that, in addition to changes in the receptor-binding specificity of the hemagglutinin, alterations of the NA are needed for the emergence of pandemic influenza viruses

Glycosylation Site Alteration in the Evolution of Influenza A (H1N1) Viruses

Influenza virus typically alters protein glycosylation in order to escape immune pressure from hosts and hence to facilitate survival in different host environments. In this study, the patterns and conservation of glycosylation sites on HA and NA of influenza A/H1N1 viruses isolated from various hosts at different time periods were systematically analyzed, by employing a new strategy combining genome-based glycosylation site prediction and 3D modeling of glycoprotein structures, for elucidation of the modes and laws of glycosylation site alteration in the evolution of influenza A/H1N1 viruses. The results showed that influenza H1N1 viruses underwent different alterations of protein glycosylation in different hosts. Two alternative modes of glycosylation site alteration were involved in the evolution of human influenza virus: One was an increase in glycosylation site numbers, which mainly occurred with high frequency in the early stages of evolution. The other was a change in the positional conversion of the glycosylation sites, which was the dominating mode with relatively low frequency in the later evolutionary stages. The mechanisms and possibly biological functions of glycosylation site alteration for the evolution of influenza A/H1N1 viruses were also discussed. Importantly, the significant role of positional alteration of glycosylation sites in the host adaptation of influenza virus was elucidated. Although the results still need to be supported by experimental data, the information here may provide some constructive suggestions for research into the glycosylation of influenza viruses as well as even the design of surveillance and the production of viral vaccines

Non-invasive imaging in the diagnosis of acute viral myocarditis

Autopsy series of consecutive cases have demonstrated an incidence of myocarditis at approximately 1–10%; on the contrary, myocarditis is seriously underdiagnosed clinically. In a traditional view, the gold standard has been myocardial biopsy. However, it is generally specific but invasive and less sensitive, mostly because of the focal nature of the disease. Thus, non-invasive approaches to detect myocarditis are necessary. The traditional diagnostic tools are electrocardiography, laboratory values, especially troponin T or I, creatine kinase and echocardiography. For a long period, nuclear technique with indium-111 antimyosin antibody has been used as a diagnostic approach. In the last years, the use of this technique has declined because of radiation exposure and 48-h delay in obtaining imaging after injection to prevent blood pool effect. Thus, a non-invasive diagnostic approach without radiation and online image availability has been awaited. Cardiac magnetic resonance imaging has these promising characteristics. With this technique, it is possible to analyse inflammation, oedema and necrosis in addition to functional parameters such as left ventricular function, regional wall motion and dimensions. Thus, cardiovascular magnetic resonance imaging has emerged as the most important imaging tool in the diagnostic procedure and the review focus on this field. But there are also advances in echocardiography and computer tomography, which are described in detail

Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock

<p>Abstract</p> <p>Background</p> <p>Molecular docking methods are commonly used for predicting binding modes and energies of ligands to proteins. For accurate complex geometry and binding energy estimation, an appropriate method for calculating partial charges is essential. AutoDockTools software, the interface for preparing input files for one of the most widely used docking programs AutoDock 4, utilizes the Gasteiger partial charge calculation method for both protein and ligand charge calculation. However, it has already been shown that more accurate partial charge calculation - and as a consequence, more accurate docking- can be achieved by using quantum chemical methods. For docking calculations quantum chemical partial charge calculation as a routine was only used for ligands so far. The newly developed Mozyme function of MOPAC2009 allows fast partial charge calculation of proteins by quantum mechanical semi-empirical methods. Thus, in the current study, the effect of semi-empirical quantum-mechanical partial charge calculation on docking accuracy could be investigated.</p> <p>Results</p> <p>The docking accuracy of AutoDock 4 using the original AutoDock scoring function was investigated on a set of 53 protein ligand complexes using Gasteiger and PM6 partial charge calculation methods. This has enabled us to compare the effect of the partial charge calculation method on docking accuracy utilizing AutoDock 4 software. Our results showed that the docking accuracy in regard to complex geometry (docking result defined as accurate when the RMSD of the first rank docking result complex is within 2 Å of the experimentally determined X-ray structure) significantly increased when partial charges of the ligands and proteins were calculated with the semi-empirical PM6 method.</p> <p>Out of the 53 complexes analyzed in the course of our study, the geometry of 42 complexes were accurately calculated using PM6 partial charges, while the use of Gasteiger charges resulted in only 28 accurate geometries. The binding affinity estimation was not influenced by the partial charge calculation method - for more accurate binding affinity prediction development of a new scoring function for AutoDock is needed.</p> <p>Conclusion</p> <p>Our results demonstrate that the accuracy of determination of complex geometry using AutoDock 4 for docking calculation greatly increases with the use of quantum chemical partial charge calculation on both the ligands and proteins.</p

Sequential analysis of global gene expression profiles in immature and in vitro matured bovine oocytes: potential molecular markers of oocyte maturation

Abstract Background Without intensive selection, the majority of bovine oocytes submitted to in vitro embryo production (IVP) fail to develop to the blastocyst stage. This is attributed partly to their maturation status and competences. Using the Affymetrix GeneChip Bovine Genome Array, global mRNA expression analysis of immature (GV) and in vitro matured (IVM) bovine oocytes was carried out to characterize the transcriptome of bovine oocytes and then use a variety of approaches to determine whether the observed transcriptional changes during IVM was real or an artifact of the techniques used during analysis. Results 8489 transcripts were detected across the two oocyte groups, of which ~25.0% (2117 transcripts) were differentially expressed (p < 0.001); corresponding to 589 over-expressed and 1528 under-expressed transcripts in the IVM oocytes compared to their immature counterparts. Over expression of transcripts by IVM oocytes is particularly interesting, therefore, a variety of approaches were employed to determine whether the observed transcriptional changes during IVM were real or an artifact of the techniques used during analysis, including the analysis of transcript abundance in oocytes in vitro matured in the presence of α-amanitin. Subsets of the differentially expressed genes were also validated by quantitative real-time PCR (qPCR) and the gene expression data was classified according to gene ontology and pathway enrichment. Numerous cell cycle linked (CDC2, CDK5, CDK8, HSPA2, MAPK14, TXNL4B), molecular transport (STX5, STX17, SEC22A, SEC22B), and differentiation (NACA) related genes were found to be among the several over-expressed transcripts in GV oocytes compared to the matured counterparts, while ANXA1, PLAU, STC1and LUM were among the over-expressed genes after oocyte maturation. Conclusion Using sequential experiments, we have shown and confirmed transcriptional changes during oocyte maturation. This dataset provides a unique reference resource for studies concerned with the molecular mechanisms controlling oocyte meiotic maturation in cattle, addresses the existing conflicting issue of transcription during meiotic maturation and contributes to the global goal of improving assisted reproductive technology

World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

BACKGROUND: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. METHODS: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40-80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. FINDINGS: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629-0·741) to 0·833 (0·783-0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40-64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. INTERPRETATION: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. FUNDING: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research