Researchers
at EMBL's European Bioinformatics Institute (EMBL-EBI) have combined their
knowledge of bacterial genetics and web search algorithms to build a DNA search
engine for microbial data. The search engine, described in a paper published in
Nature Biotechnology, could enable researchers and public health agencies to
use genome sequencing data to monitor the spread of antibiotic resistance
genes. By making this vast amount of data discoverable, the search engine could
also allow researchers to learn more about bacteria and viruses.
This
type of search could prove extremely useful for understanding disease. Take,
for example, an outbreak of food poisoning, where the cause is a Salmonella
strain containing a drug-resistance plasmid (a 'hitchhiking' DNA element that
can spread drug resistance across different bacterial species). For the first
time, BIGSI allows researchers to easily spot if and when the plasmid has been
seen before.
Google
and other search engines use natural language processing to search through
billions of websites. They are able to take advantage of the fact that human
language is relatively unchanging. By contrast, microbial DNA shows the imprint
of billions of years of evolution, so each new microbial genome can contain new
'language' that has never been seen before. The key to making BIGSI work was
finding a way to build a search index that could cope with the diversity of
microbial DNA.
See:
Posted by Dr. Tim Sandle, Pharmaceutical Microbiology
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