Dataset Information

Antigenic variability in Neuraminidase protein of Influenza A/H3N2 vaccine strains (1968 - 2009).

ABSTRACT: Antigenic drift and shift involving the surface proteins of Influenza virus gave rise to new strains that caused epidemics affecting millions of people worldwide over the last hundred years. Variations in the membrane proteins like Hemagglutinin (HA) and Neuraminidase (NA) necessitates new vaccine strains to be updated frequently and poses challenge to effective vaccine design. Though the HA protein, the primary target of the human immune system, has been well studied, reports on the antigenic variability in the other membrane protein NA are sparse. In this paper we investigate the molecular basis of antigenic drift in the NA protein of the Influenza A/H3N2 vaccine strains between 1968 and 2009 and proceed to establish correlation between antigenic drift and antigen-antibody interactions. Sequence alignments and phylogenetic analyses were carried out and the antigenic variability was evaluated in terms of antigenic distance. To study the effects of antigenic drift on the protein structures, 3D structure of NA from various strains were predicted. Also, rigid body docking protocol has been used to study the interactions between these NA proteins and antibody Mem5, a 1998 antibody.

SUBMITTER: Shil P

PROVIDER: S-EPMC3174040 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Antigenic variability in Neuraminidase protein of Influenza A/H3N2 vaccine strains (1968 - 2009).

Shil Pratip P Chavan Sameer S SS Cherian Sarah S SS

Bioinformation 20110906 2

Antigenic drift and shift involving the surface proteins of Influenza virus gave rise to new strains that caused epidemics affecting millions of people worldwide over the last hundred years. Variations in the membrane proteins like Hemagglutinin (HA) and Neuraminidase (NA) necessitates new vaccine strains to be updated frequently and poses challenge to effective vaccine design. Though the HA protein, the primary target of the human immune system, has been well studied, reports on the antigenic v ...[more]

PMID: 21938209

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Project description:Human influenza A viruses are rapidly evolving pathogens that cause substantial morbidity and mortality in seasonal epidemics around the globe. To ensure continued protection, the strains used for the production of the seasonal influenza vaccine have to be regularly updated, which involves data collection and analysis by numerous experts worldwide. Computer-guided analysis is becoming increasingly important in this problem due to the vast amounts of generated data. We here describe a computational method for selecting a suitable strain for production of the human influenza A virus vaccine. It interprets available antigenic and genomic sequence data based on measures of antigenic novelty and rate of propagation of the viral strains throughout the population. For viral isolates sampled between 2002 and 2007, we used this method to predict the antigenic evolution of the H3N2 viruses in retrospective testing scenarios. When seasons were scored as true or false predictions, our method returned six true positives, three false negatives, eight true negatives, and one false positive, or 78% accuracy overall. In comparison to the recommendations by the WHO, we identified the correct antigenic variant once at the same time and twice one season ahead. Even though it cannot be ruled out that practical reasons such as lack of a sufficiently well-growing candidate strain may in some cases have prevented recommendation of the best-matching strain by the WHO, our computational decision procedure allows quantitative interpretation of the growing amounts of data and may help to match the vaccine better to predominating strains in seasonal influenza epidemics. Importance: Human influenza A viruses continuously change antigenically to circumvent the immune protection evoked by vaccination or previously circulating viral strains. To maintain vaccine protection and thereby reduce the mortality and morbidity caused by infections, regular updates of the vaccine strains are required. We have developed a data-driven framework for vaccine strain prediction which facilitates the computational analysis of genetic and antigenic data and does not rely on explicit evolutionary models. Our computational decision procedure generated good matches of the vaccine strain to the circulating predominant strain for most seasons and could be used to support the expert-guided prediction made by the WHO; it thus may allow an increase in vaccine efficacy.

Dataset Information

Antigenic variability in Neuraminidase protein of Influenza A/H3N2 vaccine strains (1968 - 2009).

Publications

Antigenic variability in Neuraminidase protein of Influenza A/H3N2 vaccine strains (1968 - 2009).

Similar Datasets

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