Study predicts less than 10 per cent of E. coli O157 cattle isolates can cause disease in humans

Hi all…I’ve come across another study which most drinking water/public health providers will never see but it contains an extremely important finding. Previous watershed surveys have revealed that E. coli O157/E. coli O157:H7 are detected relatively infrequently (less than 5% of samples). While it is not typically present it would nonetheless be expected that disease outbreaks would occur at rates higher than observed. This new study helps to explain why Walkerton E. coli O157:H7 type outbreaks don’t occur more often. The authors report only a minor subset (less than 10%) of bovine E. coli O157 isolates analyzed were predicted to have the potential to cause human disease and they conclude “…none of the cattle isolates (apart from outbreak trace-back isolates) achieved very high human association probabilities (>0.9), potentially indicating that those posing a serious zoonotic threat are very rare.” 

Bill

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Support vector machine applied to predict the zoonotic potential of E. coli O157 cattle isolates

Nadejda Lupolova, Timothy J. Dallman, Louise Matthews, James L. Bono, and David L. Gally

Published online before print September 19, 2016, doi: 10.1073/pnas.1606567113 PNAS September 19, 2016

http://www.pnas.org/content/early/2016/09/15/1606567113.abstract.html?etoc

Abstract

“Sequence analyses of pathogen genomes facilitate the tracking of disease outbreaks and allow relationships between strains to be reconstructed and virulence factors to be identified. However, these methods are generally used after an outbreak has happened. Here, we show that support vector machine analysis of bovine E. coli O157 isolate sequences can be applied to predict their zoonotic potential, identifying cattle strains more likely to be a serious threat to human health. Notably, only a minor subset (less than 10%) of bovine E. coli O157 isolates analyzed in our datasets were predicted to have the potential to cause human disease; this is despite the fact that the majority are within previously defined pathogenic lineages I or I/II and encode key virulence factors. The predictive capacity was retained when tested across datasets. The major differences between human and bovine E. coli O157 isolates were due to the relative abundances of hundreds of predicted prophage proteins. This finding has profound implications for public health management of disease because interventions in cattle, such a vaccination, can be targeted at herds carrying strains of high zoonotic potential. Machine-learning approaches should be applied broadly to further our understanding of pathogen biology.”