Published January 7, 2019 | Version v1
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Data from: Using the wax moth larva Galleria mellonella infection model to detect emerging bacterial pathogens

  • 1. Stony Brook University
  • 2. University of Exeter
  • 3. University of Bath

Description

Climate change, changing farming practices, social and demographic changes and rising levels of antibiotic resistance are likely to lead to future increases in opportunistic bacterial infections that are more difficult to treat. Uncovering the prevalence and identity of pathogenic bacteria in the environment is key to assessing transmission risks. We describe the first use of the Wax moth larva Galleria mellonella, a well-established model for the mammalian innate immune system, to selectively enrich and characterize pathogens from coastal environments in the South West of the UK. Whole-genome sequencing of highly virulent isolates revealed amongst others a Proteus mirabilis strain carrying the Salmonella SGI1 genomic island not reported from the UK before and the recently described species Vibrio injenensis hitherto only reported from human patients in Korea. Our novel method has the power to detect bacterial pathogens in the environment that potentially pose a serious risk to public health.

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Is cited by
10.7717/peerj.6150 (DOI)