230 research outputs found

    PCR for the detection of pathogens in neonatal early onset sepsis.

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    BACKGROUND: A large proportion of neonates are treated for presumed bacterial sepsis with broad spectrum antibiotics even though their blood cultures subsequently show no growth. This study aimed to investigate PCR-based methods to identify pathogens not detected by conventional culture. METHODS: Whole blood samples of 208 neonates with suspected early onset sepsis were tested using a panel of multiplexed bacterial PCRs targeting Streptococcus pneumoniae, Streptococcus agalactiae (GBS), Staphylococcus aureus, Streptococcus pyogenes (GAS), Enterobacteriaceae, Enterococcus faecalis, Enterococcus faecium, Ureaplasma parvum, Ureaplasma urealyticum, Mycoplasma hominis and Mycoplasma genitalium, a 16S rRNA gene broad-range PCR and a multiplexed PCR for Candida spp. RESULTS: Two-hundred and eight samples were processed. In five of those samples, organisms were detected by conventional culture; all of those were also identified by PCR. PCR detected bacteria in 91 (45%) of the 203 samples that did not show bacterial growth in culture. S. aureus, Enterobacteriaceae and S. pneumoniae were the most frequently detected pathogens. A higher bacterial load detected by PCR was correlated positively with the number of clinical signs at presentation. CONCLUSION: Real-time PCR has the potential to be a valuable additional tool for the diagnosis of neonatal sepsis

    Viral factors in influenza pandemic risk assessment

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    The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk

    Canalization of the evolutionary trajectory of the human influenza virus

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    Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. Antigenic evolution occurs in the context of a two-dimensional 'antigenic map', while genetic evolution shows a characteristic ladder-like genealogical tree. Here, we use a large-scale individual-based model to show that evolution in a Euclidean antigenic space provides a remarkable correspondence between model behavior and the epidemiological, antigenic, genealogical and geographic patterns observed in influenza virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. Thus, selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable and hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure

    Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses

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    Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny

    Global circulation patterns of seasonal influenza viruses vary with antigenic drift.

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    Understanding the spatiotemporal patterns of emergence and circulation of new human seasonal influenza virus variants is a key scientific and public health challenge. The global circulation patterns of influenza A/H3N2 viruses are well characterized, but the patterns of A/H1N1 and B viruses have remained largely unexplored. Here we show that the global circulation patterns of A/H1N1 (up to 2009), B/Victoria, and B/Yamagata viruses differ substantially from those of A/H3N2 viruses, on the basis of analyses of 9,604 haemagglutinin sequences of human seasonal influenza viruses from 2000 to 2012. Whereas genetic variants of A/H3N2 viruses did not persist locally between epidemics and were reseeded from East and Southeast Asia, genetic variants of A/H1N1 and B viruses persisted across several seasons and exhibited complex global dynamics with East and Southeast Asia playing a limited role in disseminating new variants. The less frequent global movement of influenza A/H1N1 and B viruses coincided with slower rates of antigenic evolution, lower ages of infection, and smaller, less frequent epidemics compared to A/H3N2 viruses. Detailed epidemic models support differences in age of infection, combined with the less frequent travel of children, as probable drivers of the differences in the patterns of global circulation, suggesting a complex interaction between virus evolution, epidemiology, and human behaviour.T.B. was supported by a Newton International Fellowship from the Royal Society and through NIH U54 GM111274. S.R. was supported by MRC (UK, Project MR/J008761/1), Wellcome Trust (UK, Project 093488/Z/10/Z), Fogarty International Centre (USA, R01 TW008246‐01), DHS (USA, RAPIDD program), NIGMS (USA, MIDAS U01 GM110721‐01) and NIHR (UK, Health Protection Research Unit funding). The Melbourne WHO Collaborating Centre for Reference and Research on Influenza was supported by the Australian Government Department of Health and thanks N. Komadina and Y.‐M. Deng. The Atlanta WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza was supported by the U.S. Department of 13 Health and Human Services. NIV thanks A.C. Mishra, M. Chawla‐Sarkar, A.M. Abraham, D. Biswas, S. Shrikhande, AnuKumar B, and A. Jain. Influenza surveillance in India was expanded, in part, through US Cooperative Agreements (5U50C1024407 and U51IP000333) and by the Indian Council of Medical Research. M.A.S. was supported through NSF DMS 1264153 and NIH R01 AI 107034. Work of the WHO Collaborating Centre for Reference and Research on Influenza at the MRC National Institute for Medical Research was supported by U117512723. P.L., A.R. & M.A.S were supported by EU Seventh Framework Programme [FP7/2007‐2013] under Grant Agreement no. 278433-­‐PREDEMICS and ERC Grant agreement no. 260864. C.A.R. was supported by a University Research Fellowship from the Royal Society.This is the author accepted manuscript. It is currently under infinite embargo pending publication of the final version

    Genome-wide evolutionary dynamics of influenza B viruses on a global scale

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    The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally
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