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Life Technologies Establishes International Influenza Network

Published: Friday, February 01, 2013
Last Updated: Friday, February 01, 2013
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Scientists at leading public health agencies and research institutes collaborate to develop faster, more reliable flu subtyping methods.

Life Technologies Corporation has announced the establishment of the Global Influenza Network, a partnership including scientists at a number of the world's leading government public health organizations, veterinary agencies and research institutes in a collaborative effort to increase the speed and efficiency of influenza monitoring and vaccine development.

Members of the network are sharing tools, experience and data using the Ion Personal Genome Machine (PGM™) semiconductor sequencing platform.

"Life Technologies exhibited leadership in infectious disease tracking when our scientists worked alongside federal officials to identify the cause of H1N1 outbreak in 2008," said Gregory T. Lucier, Chairman and Chief Executive Officer of Life Technologies.

Lucier continued, "We are very proud to now bring together a group of such distinguished organizations to tackle the continued threat of influenza worldwide."

Participating scientists include: Steve Glavas, head of the NGS Platform, and Mia Brytting, Ph.D., head of the microbial typing unit at the Swedish Institute for Communicable Disease Control (SMI); Gabriele Vaccari, Ph.D., researcher at the Istituto Superiore di Sanita in Rome; Mary Lea Killian, microbiologist at the U.S. National Veterinary Service Laboratories in Ames, Iowa; and David Wentworth at the J. Craig Venter Institute in Rockville, Md.

Partnership Develops Faster, More Reliable Flu Subtyping Methods
Annual seasonal influenza epidemics cause approximately 3 to 5 million cases of severe illness and 250,000 to 500,000 deaths, according to the World Health Organization (WHO).

Pandemics caused by novel influenza strains can result in staggering death tolls; the "Spanish flu" of 1918 is believed to have killed 40 million people, or 3 percent of the global population, according to the WHO.

Each year, public health agencies around the world collect samples from infected individuals and share data about flu subtypes circulating in their regions.

The pooled data are used by the WHO to determine the strains used to design a vaccine that will be effective against that year's epidemic. Costs of sequencing, however, have limited data set to about 20 percent of the patient samples collected.

"Using next generation sequencing technology makes whole influenza genome sequencing much easier, and much less expensive than older sequencing techniques, when used appropriately," said Glavas.

Scientists in the Global Influenza Network also believe that by sequencing all patient samples collected ahead of the flu season, they will be able to detect emerging strains earlier and focus resources on areas of the world where these strains are most prevalent in order to better contain new threats.

An additional benefit of semiconductor sequencing is the technologies' superior speed over conventional methods. Therefore, sequencing data can be collected in a smaller time window prior to vaccine production, which can also guide the production of vaccines so they more effectively target the strains most prevalent in the coming flu season.

"Now we can easily fully characterize influenza causing severe outbreaks," said Brytting.

Network Scientists Confirm Protocol's Accuracy and Economic
The current collaboration is a pilot program to evaluate the efficacy of influenza virus typing by semiconductor sequencing on Life Technologies' Ion Torrent platform, the Ion PGM™ sequencer.

After implementing Life Technologies' protocol for whole genome sequencing of Influenza A virus, the network partners determined it to be: (1) accurate; (2) highly sensitive and (3) economical (less than $100 per isolate) because it enables scientists to multiplex at least 10 samples in a single run on the Ion PGM™ sequencer.

Global Influenza Network partners have agreed to share their data and experiences in order to refine the initial protocol, if needed. The results of the collaborative study will be submitted to a peer-reviewed research journal for publication.

The Ion Personal Genome Machine (PGM™) is Research Use Only and not intended for use in diagnostic procedures.

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