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Amino acids transitioning of 2009 H1N1pdm in Taiwan from 2009 to 2011.

ABSTRACT: A swine-origin influenza A was detected in April 2009 and soon became the 2009 H1N1 pandemic strain (H1N1pdm). The current study revealed the genetic diversity of H1N1pdm, based on 77 and 70 isolates which we collected, respectively, during the 2009/2010 and 2010/2011 influenza seasons in Taiwan. We focused on tracking the amino acid transitioning of hemagglutinin (HA) and neuraminidase (NA) genes in the early diversification of the virus and compared them with H1N1pdm strains reported worldwide. We identified newly emerged mutation markers based on A/California/04/2009, described how these markers shifted from the first H1N1pdm season to the one that immediately followed, and discussed how these observations may relate to antigenicity, receptor-binding, and drug susceptibility. It was found that the amino acid mutation rates of H1N1pdm were elevated, from 9.29×10(-3) substitutions per site in the first season to 1.46×10(-2) in the second season in HA, and from 5.23×10(-3) to 1.10×10(-2) in NA. Many mutation markers were newly detected in the second season, including 11 in HA and 8 in NA, and some were found having statistical correlation to disease severity. There were five noticeable HA mutations made to antigenic sites. No significant titer changes, however, were detected based on hemagglutination inhibition tests. Only one isolate with H275Y mutation known to reduce susceptibility to NA inhibitors was detected. As limited Taiwanese H1N1pdm viruses were isolated after our sampling period, we gathered 8,876 HA and 6,017 NA H1N1pdm sequences up to April 2012 from NCBI to follow up the dynamics of mentioned HA mutations. While some mutations described in this study seemed to either settle in or die out in the 2011-2012 season, a number of them still showed signs of transitioning, prompting the importance of continuous monitoring of this virus for more seasons to come.

SUBMITTER: Chen GW

PROVIDER: S-EPMC3454337 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Amino acids transitioning of 2009 H1N1pdm in Taiwan from 2009 to 2011.

Chen Guang-Wu GW Tsao Kuo-Chien KC Huang Chung-Guei CG Gong Yu-Nong YN Chang Shih-Cheng SC Liu Yi-Chun YC Wu Hsiao-Han HH Yang Shu-Li SL Lin Tzou-Yien TY Huang Yhu-Chering YC Shih Shin-Ru SR

PloS one 20120924 9

A swine-origin influenza A was detected in April 2009 and soon became the 2009 H1N1 pandemic strain (H1N1pdm). The current study revealed the genetic diversity of H1N1pdm, based on 77 and 70 isolates which we collected, respectively, during the 2009/2010 and 2010/2011 influenza seasons in Taiwan. We focused on tracking the amino acid transitioning of hemagglutinin (HA) and neuraminidase (NA) genes in the early diversification of the virus and compared them with H1N1pdm strains reported worldwide ...[more]

PMID: 23029335

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Project description:BackgroundMathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches.MethodsWe used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability.ResultsReal-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model.ConclusionsOur results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models.

Dataset Information

Amino acids transitioning of 2009 H1N1pdm in Taiwan from 2009 to 2011.

Publications

Amino acids transitioning of 2009 H1N1pdm in Taiwan from 2009 to 2011.

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