Influenza vaccine strain selection and recent studies on the global migration of seasonal influenza viruses

Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
Vaccine (Impact Factor: 3.77). 09/2008; DOI: 10.1016/j.vaccine.2008.07.078
Source: PubMed


Annual influenza epidemics in humans affect 5–15% of the population, causing an estimated half million deaths worldwide per year [Stohr K. Influenza—WHO cares. Lancet Infectious Diseases 2002;2(9):517]. The virus can infect this proportion of people year after year because the virus has an extensive capacity to evolve and thus evade the immune response. For example, since the influenza A(H3N2) subtype entered the human population in 1968 the A(H3N2) component of the influenza vaccine has had to be updated almost 30 times to track the evolution of the viruses and remain effective. The World Health Organization Global Influenza Surveillance Network (WHO GISN) tracks and analyzes the evolution and epidemiology of influenza viruses for the primary purpose of vaccine strain selection and to improve the strain selection process through studies aimed at better understanding virus evolution and epidemiology. Here we give an overview of the strain selection process and outline recent investigations into the global migration of seasonal influenza viruses.

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Available from: Masato Tashiro, Oct 08, 2015
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    • "In human influenza viruses, the vaccine strain for target season t is identified at the end of season t − 1 (pre-target season) from the epidemic viruses isolated by then (Treanor, 2004; Russell et al., 2008a). To identify, retrospectively, the most effective vaccine strain for each target season of 2001.0 ≤ t ≤ 2014.5, the average antigenic distance was computed between each of the strains isolated in seasons 1992.0 to t − 1 and the epidemic viruses sampled in season t. "
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    ABSTRACT: H3N2 human influenza A virus causes epidemics of influenza mainly in the winter season in temperate regions. Since the antigenicity of this virus evolves rapidly, several attempts have been made to predict the major amino acid sequence of hemagglutinin 1 (HA1) in the target season of vaccination. However, the usefulness of predicted sequence was unclear because its relationship to the antigenicity was unknown. Here the antigenic model for estimating the degree of antigenic difference (antigenic distance) between amino acid sequences of HA1 was integrated into the process of selecting vaccine strains for H3N2 human influenza A virus. When the effectiveness of a potential vaccine strain for a target season was evaluated retrospectively using the average antigenic distance between the strain and the epidemic viruses sampled in the target season, the most effective vaccine strain was identified mostly in the season one year before the target season (pre-target season). Effectiveness of actual vaccines appeared to be lower than that of the strains randomly chosen in the pre-target season on average. It was recommended to replace the vaccine strain for every target season with the strain having the smallest average antigenic distance to the others in the pre-target season. The procedure of selecting vaccine strains for future epidemic seasons described in the present study was implemented in the influenza virus forecasting system (INFLUCAST) (
    Meta Gene 06/2015; 4. DOI:10.1016/j.mgene.2015.03.003
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    • "e grouped under B / Yam and B / Vic . Lineages . Others that were isolated before 1983 were not included in this classification . Numbers at each node of the tree show bootstrap percentages obtained after 1 , 000 replicates . been identified " East and Southeast Asian circulation network " as a leading migration route to Europe and North America [ Russell et al . , 2008 ] ."
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    ABSTRACT: Influenza viruses are known as continuing threats to human public health every year worldwide. Evolutionary dynamics of influenza B viruses in humans are in a unique progression having two lineages; B/Yam and B/Vic-like viruses, which are circulating simultaneously worldwide. There is a considerable lack of data on influenza B viruses circulating in Saudi Arabia. During the winter-spring season of 2010-2011, 80 nasopharyngeal aspirates were collected from hospitalized patients with flu-like symptoms in Riyadh. Screening of samples by one-step RT-PCR identified three (3.8%) influenza B viruses. Sequencing of hemagglutinin (HA) and neuraminidase (NA) genes was performed to analyze influenza B viruses circulating in Riyadh as compared to the globally circulating strains. Several common and six unique amino acid substitutions were observed for both HA and NA genes of influenza B Saudi strains. Three unique substitutions (T182A, D196N, and K254R) were identified in HA gene of the B/Yam-like Riyadh strains. In NA gene, a unique common substitution (D53G) was found in all Riyadh strains, while two unique substitutions (L38P, G233R) were recognized only in B/Vic-like Riyadh strains. Riyadh strains were also found to contain N-glycosylation site in HA gene of both B/Vic and B/Yam lineages at positions 197-199 (NET) and 196-198 (NNK/DNK), respectively. The significance of these mutations on the antigenicity of both lineages is discussed herein. The unique changes observed in HA and NA genes of influenza B Riyadh strains support strongly the need for continuous surveillance and monitoring of new evolving strains that might pose threat to the Saudi community. J. Med. Virol. © 2013 Wiley Periodicals, Inc.
    Journal of Medical Virology 06/2014; 86(6). DOI:10.1002/jmv.23819 · 2.35 Impact Factor
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    • "As input, we are often given a set of aligned genetic sequences for which we wish to work out the pattern of ancestry. This analysis plays an important role in, for example, drug or vaccine development (McHardy & Adams, 2009; Russell et al., 2008). With the cost of sequencing decreasing rapidly due to next generation sequencing technologies (Metzker, 2010), more and more sequences are becoming available and deposited in sequence repositories such as GenBank (Benson et al., 2011). "
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    ABSTRACT: Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000-8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under:
    PeerJ 06/2013; 1(2):e89. DOI:10.7717/peerj.89 · 2.11 Impact Factor
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