Funding period: 2022–2024
Leads: Catherine Carrillo and Burton Blais
Total GRDI funding: $40,000
This project will use leading edge sequencing technology (PoreSippr) for real-time identification and risk profiling of verotoxigenic Escherichia coli (VTEC). VTEC toxins are currently thought to be an important factor for assessing the risk of these organisms. It is challenging to characterize toxins with current sequencing methods due to lack of availability of comprehensive toxin databases, and difficulty sequencing these genes. In fact, in a recent study encompassing international participants, none of the laboratories were able to type VTEC toxins based on whole-genome sequencing data. Strains recovered in CFIA food testing programs often have unusual variants of toxins that are incorrectly classified using automated tools. This project will solve this problem by providing a comprehensive public database of curated verotoxin genes, as well as a method for rapid VTEC profiling based on long-read sequencing (PoreSippr). The ultimate goal is to ensure the availability of a method meeting broader Canadian food safety regulatory needs with respect to risk characterization of VTEC recovered from foods.
Research tool/process
- PoreSippR for risk profiling of VTEC. The PoreSippR method uses leading-edge long-read Oxford Nanopore sequencing technology for real-time identification and risk profiling of verotoxigenic E. coli (VTEC). This method revolutionizes the speed and accuracy of VTEC genome characterization for risk-assessment purposes. From isolate preparation to Nanopore sequencing, the entire PoreSippR protocol can provide the desired characterization of STEC strains within a time frame of ~8 hours. This indicates that the entire PoreSippR workflow and STEC characterization can be completed within 1 working day, at costs similar to current methodology. This technique has the potential to be implemented in food testing laboratories, where it could replace methods like CHAS for the rapid characterization of VTEC isolates identified in food testing programs.
Dataset/database
- Shiga Toxin Allele Database (StxDB): A comprehensive, curated database of Shiga toxins including all know nucleotide and protein sequence variants to enable accurate determination of Shiga-toxin variants. This database has been curated to provide accession numbers for representative genomes to enable database users to assess reliability of results. Contributors: Sarah Clarke, Catherine Carrillo, Burton Blais, Adam Koziol, Noor Shubair, Mathu Malar, Liam Brown, Ashley Cooper and Alex Gill.
Contact us
For additional information, please contact:
Genomics R&D Initiative
Email: info@grdi-irdg.collaboration.gc.ca