Sunday, December 31, 2006
Evolution Of Influenza A Virus (PR + Paper)
A PLoS Pathogens press release:
An understanding of the evolutionary dynamics of the influenza virus determines scientists' ability to survey and control the virus. In a new study, published online in the open-access journal PLoS Pathogens, Dr. Eddie C. Holmes* of the Department of Biology at Pennsylvania State University and colleagues at the National Institutes of Health, the Wordsworth Center and the Institute for Genomic Research used genomic analysis to investigate the evolutionary properties of the H3N2 subtype of human influenza A virus.
The authors, in the first population-based study of its kind, collected a sample group of 413 complete influenza genomes from across New York State. Comparative analysis of the samples revealed genetically distinct viral strains circulate across the state within any one season and occasionally exchange genes through reassortment.
These results indicate that adaptive evolution occurs only sporadically in influenza virus, and that influenza virus diversity and evolution is strongly affected by chance events, such as reassortment between strains coinfecting a host or the introduction of a particular variant from elsewhere. These factors make predicting future patterns of influenza virus evolution more difficult, as vaccine strain selection then becomes dependent upon intensive surveillance, whole-genome sequencing, and phenotypic analysis.
Based on the paper:
Stochastic Processes Are Key Determinants of Short-Term Evolution in Influenza A Virus
Citation: Nelson MI, Simonsen L, Viboud C, Miller MA, Taylor J, et al. (2006) Stochastic Processes Are Key Determinants of Short-Term Evolution in Influenza A Virus. PLoS Pathog 2(12): e125 DOI: 10.1371/journal.ppat.0020125
A comparative analysis of 413 complete genomes of the H3N2 subtype of human influenza A virus sampled from New York State, United States, the largest and first population-based study of its kind, reveals that viral evolution within epidemic seasons is dominated by the random importation of genetically different viral strains from other geographic areas, rather than by natural selection favoring local strains able to escape the human immune response. Multiple clades of genetically distinct viral strains cocirculate across the entire state within any season and occasionally exchange genes through reassortment. Both genetic diversity and geographic viral "traffic" are extensive within epidemics. Therefore, the evolution of influenza A virus is strongly shaped by random migration and reassortment and is far harder to predict than previously realized. Consequently, intensive sampling and whole-genome sequencing are essential for selecting viral strains for future vaccine production.
Understanding the evolutionary dynamics of influenza A virus is central to its surveillance and control. While immune-driven antigenic drift is a key determinant of viral evolution across epidemic seasons, the evolutionary processes shaping influenza virus diversity within seasons are less clear. Here we show with a phylogenetic analysis of 413 complete genomes of human H3N2 influenza A viruses collected between 1997 and 2005 from New York State, United States, that genetic diversity is both abundant and largely generated through the seasonal importation of multiple divergent clades of the same subtype. These clades cocirculated within New York State, allowing frequent reassortment and generating genome-wide diversity. However, relatively low levels of positive selection and genetic diversity were observed at amino acid sites considered important in antigenic drift. These results indicate that adaptive evolution occurs only sporadically in influenza A virus; rather, the stochastic processes of viral migration and clade reassortment play a vital role in shaping short-term evolutionary dynamics. Thus, predicting future patterns of influenza virus evolution for vaccine strain selection is inherently complex and requires intensive surveillance, whole-genome sequencing, and phenotypic analysis.
A 2003 Letter to Nature:
Ecological and immunological determinants of influenza evolution
Neil M. Ferguson, Alison P. Galvani and Robin M. Bush
Nature 422, 428-433 (27 March 2003) | doi:10.1038/nature01509; Received 18 November 2002; Accepted 21 February 2003
In pandemic and epidemic forms, influenza causes substantial, sometimes catastrophic, morbidity and mortality. Intense selection from the host immune system drives antigenic change in influenza A and B, resulting in continuous replacement of circulating strains with new variants able to re-infect hosts immune to earlier types. This 'antigenic drift'1 often requires a new vaccine to be formulated before each annual epidemic. However, given the high transmissibility and mutation rate of influenza, the constancy of genetic diversity within lineages over time is paradoxical. Another enigma is the replacement of existing strains during a global pandemic caused by 'antigenic shift' - the introduction of a new avian influenza A subtype into the human population1. Here we explore ecological and immunological factors underlying these patterns using a mathematical model capturing both realistic epidemiological dynamics and viral evolution at the sequence level. By matching model output to phylogenetic patterns seen in sequence data collected through global surveillance2, we find that short-lived strain-transcending immunity is essential to restrict viral diversity in the host population and thus to explain key aspects of drift and shift dynamics.
*Info on Eddie C. Holmes (abridged):
"My research integrates ideas from a number of different fields, most notably evolutionary genetics, virology and the ecology of infectious disease. I am currently concentrating on three main areas, using RNA virus study systems: Evolutionary genetics, Comparative genomics and Molecular epidemiology"
Technorati: evolutionary, dynamics, influenza, virus, study, plos, pathogens, biology, pennsylvania, state, university, holmes, genetics, research, human, a, new york, genome, strain, adaptive, evolution, diversity, immune, stochastic, virology, ecology