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Big Data Could Help Prevent The Spread Of Influenza

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Influenza

Recently, a study conducted at the University of Zurich in Switzerland, in collaboration with researchers around the world, compared data taken from a number of different publications on Influenza A virus host molecules necessary for virus replication.

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December 11, 2015 | by Sarah Massey, M.Sc.

Flu epidemics occur on almost an annual basis, and to complicate efforts to predict which strains will be dominant in any given year, sometimes novel virus strains can contribute to the spread of a global pandemic. Influenza A viruses that carry multiple resistance to currently-available flu medications have been an increasingly problem in recent years.

As with other viruses, influenza relies on the cellular machinery found in its host’s respiratory cells in order to replicate and spread. In light of this mode of proliferation, researchers have focused on identifying the host cell factors necessary for the virus, in order to block the mechanism and stop the spread of the infection.

Recently, a study conducted at the University of Zurich in Switzerland, in collaboration with researchers around the world, compared data taken from a number of different publications on influenza A virus host molecules necessary for virus replication. The studies all contained large amounts of data focused on the genomic and proteomic aspects of the host cells required by the virus for survival.

After analyzing these huge datasets, the researchers were successful in identifying 20 novel molecules within the host cell, that facilitate the growth and replication of influenza A viruses. “These unchangeable host proteins are vital for the replication of the viruses,” said Professor Silke Stertz from the Institute of Medical Virology at the University of Zurich. “We can now use these to stop the virus from spreading further.”



Just one of the novel host proteins discovered by Stertz and his colleagues was UBR4; this protein is required by the virus for transportation of a number of viral proteins to the host cell membrane, in order to generate new viral particles. The researchers say that nearly 20,000 new influenza virions can be generated after infection of just one host cell.

The researchers determined that blocking the function of UBR4 would prevent the virus from replicating inside the host cell. When the UBR4 protein was blocked in mice, the progression of the disease was slowed and replication of the virus was dampened.

The researchers believe that the study shows considerable evidence that blocking host molecules needed for virus replication may be an effective treatment options for patients with resistant influenza A virus infections. “We expect the approach described in this study and the use of 'big data' to bridge the gap between biomedical research and therapeutic development, and facilitate fresh insights into previously unanswered medical questions,” said Sumit Chanda, a co-author on the publication and a researcher at Sanford Burnham Prebys Medical Discovery Institute in California.

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Keywords: Big Data, Influenza, Virus


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