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Using Big Data to Combat Flu

2015-12-14
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SBP has helped lead an international team of academic and pharmaceutical scientists that have tapped into publically available large-scale ‘Omics’ databases to identify new targets to treat influenza — the virus that causes annual epidemics and occasional pandemics. The study, published in Cell Host and Microbe, reflects a breakthrough approach using advanced computational designs to identify new factors that can be targeted to prevent viruses from spreading. The research team also created a website with open access for scientists to cull additional host-targets to develop the next-generation of anti-influenza drugs.


Denying influenza access to host resources is like preventing an invader from “living off the land.” This approach, the scientists reported, could prove to be even more effective than trying to directly block the virus.


“Traditionally, physicians have treated the flu with drugs that directly block the influenza virus,” said Dr. Chanda. “Although these drugs have been helpful, many patients fail to respond because viruses, especially IAV, can mutate, rendering them resistant to available drugs. Our research efforts are focused on finding unalterable host molecules—the ones within our bodies—that viruses hijack to spread and create full blown infections.”


Influenza viruses cannot replicate on their own. They can only carry a few genes—about a dozen or so—compared to a human genome comprising more than 20,000 genes. To ensure their survival, flu viruses rely on co-opting molecular machines in the infected host, which they use to their advantage to grow and spread.


Details of the big data approach were given in the Cell Host and Microbe article: “[We] performed a meta-analysis of data from eight published RNAi screens and integrated these data with three protein interaction datasets, including one generated within the context of this study. Further integration of these data with global virus-host interaction analyses revealed a functionally validated biochemical landscape of the influenza-host interface, which can be queried through a simplified and customizable web portal.”


The study also showed that blocking UBR4 in human cells (in vitro) and mice (in vivo) reduced IAV replication and pathogenesis, establishing proof-of-concept of the strategy to target UBR4 as an influenza treatment. “The putative ubiquitin ligase UBR4,” the article noted, “associates with the viral M2 protein and promotes apical transport of viral proteins.”


The article concluded that “the integrative analysis of influenza OMICs datasets illuminates a viral-host network of high-confidence human proteins that are essential for influenza A virus replication.”


“We anticipate that the approach described in this study, which is packaged as an accessible web interface, will provide a bridge for those on the frontlines of biomedical discovery and therapeutic development to leverage ‘big data’ and achieve transformative treatments for unmet medical needs,” added Dr. Chanda.

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