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The disease outbreak detection system of the future

Biotechnology and biochemistry Genes and genomes Bacteria and microorganisms Food safety Computer calculations
An internet-based tool can analyse the genetic material of bacteria and help detect disease outbreaks as well as find the source of an outbreak. The tool uses a new technique and was developed as part of a PhD project at the National Food Institute, Technical University of Denmark.

E. coli bacteria co-exist with humans and animals in harmless symbiosis, however, every year they also cause infections and deaths. Disease outbreaks caused by E. coli most commonly occur after contact with contaminated food or water. A recent example of a disease outbreak caused by E. coli comes from Germany, where, in 2011, several thousand people were contaminated and 50 deaths were recorded.

Disease outbreaks caused by bacteria can never completely be avoided, however, their extent can be minimised by quickly detecting them and locating the source. As part of his PhD project, Rolf Sommer Kaas from the National Food Institute has developed a freely accessible internet-based tool, CSI Phylogeny. The tool can analyse bacteria’s genetic material, e.g. that of E. coli, and determine the bacterial evolutionary tree, i.e. how the bacteria are related. This information can be used as a starting point for quickly finding the outbreak source.

Reveals the relatedness of bacteria

There are many different types of E. coli. Identifying the type is important as it is one of the main elements of detecting the outbreak and locating its source. However, the classical typing method is a relatively expensive solution and does not render all the information about the bacterium you get today by DNA sequencing the bacterium’s genome. Every time a bacterium reproduces mutations occur, and the mutations can be analysed by DNA sequencing. This allows researchers to determine the relatedness of bacteria in an outbreak and thus identify the contamination source.

As an innovation, the tool developed can create these evolutionary trees from sequencing data gathered by different sequencing techniques. Undertaking this kind of analysis process was so far not possible. With the studies and findings from this PhD project as well as any other available information in this area researchers can develop an automated disease outbreak detection system.

Tailored for the use of medical professionals

In future this internet-based tool will be an important tool for tracing infections and reducing their number. Primary target groups are epidemiologists, medical doctors and clinical microbiologists.

In addition, the PhD project examines what the maximum difference between two bacteria’s genomes can be for them to be considered related to the same outbreak. Ten different E. coli outbreaks were analysed, however, no clear conclusion was reached. There are, though, indications that the limit is around a difference of 100 mutations between two bacteria. In order to come to a clear conclusion further studies are needed.

Read more

See Rolf Sommer Kaas’ PhD thesis: Whole Genome Epidemiological Typing of Escherichia coli (pdf).

Read more about the freely accessible tool CSI Phylogeny.