Using software to compare genetic information in bacterial isolates from animals and people, researchers have predicted that less than 10% of Escherichia coli 0157:H7 strains are likely to have the potential to cause human disease. According to Nadejda Lupolova, from the University of Edinburgh, Scotland, and colleagues, "machine-learning approaches have tremendous potential to interrogate complex genome information for which specific attributes of the organism, such as disease or isolation host, are known." The researchers published the results of their study in Proceedings of the National Academy of Sciences. Although most E. coli strains live in the gastrointestinal tracts of people and animals without causing disease, infection with E. coli 0157 is associated with serious illness in people. E. coli 0157 was first identified as a cause of disease in the United States in 1982, during an investigation into an outbreak of hemorrhagic colitis.
Tonya Riley of Inverse reports that artificial intelligence is already well on its way to being the future of food service, but what if it could also do things like prevent foodborne illnesses, such as E. coli? Researchers at University of Edinburgh say they've designed software to do just that. The A.I. compares the genetic signatures of E. coli samples that have caused infection in humans to bacterial samples from humans and animals. The technology will allow researchers to identify deadly strains of E. coli before the threat becomes an outbreak. "Our findings indicate that the most dangerous E. coli O157 strains may in fact be very rare in the cattle reservoir, which is reassuring," University of Edinburgh Professor David Gally said in a press release.
A team of researchers has found a new way to detect dangerous strains of bacteria, potentially preventing outbreaks of food poisoning. The team developed a method that utilizes machine learning and tested it with isolates of Escherichia coli strains. The details are in a paper that was just published in the journal Proceedings of the National Academy of Sciences. Most strains of Escherichia coli are harmless and naturally found in the human body. There are pathogenic strains, however, and they are a rising health concern.
Machine learning can predict strains of bacteria likely to cause food poisoning outbreaks, research has found. The study – which focused on harmful strains of E. coli bacteria – could help public health officials to target interventions and reduce risk to human health. Researchers at the University of Edinburgh's Roslin Institute used software that compares genetic information from bacterial samples isolated from both animals and people. The software learns the DNA signatures that are associated with E. coli samples that have caused outbreaks of infection in people. It can then pick out the animal strains that have these signatures, which are therefore likely to be a threat to human health.