Whole genome sequencing to discover foodborne pathogen source.
- Determination of a clonal mutation substitution rate -
Bacteria multiply by binary fission, or simply put, by dividing themselves in two daughter cells called clones; however before the division can take place, the cell must replicate its genetic material and this process is not without error, and minor changes accumulate in the DNA with time. Subtyping of bacterial isolates is an essential tool used in tracing the source of a foodborne pathogen to the probable source of contamination, and this is essential for initiating a recall, assessing consumer exposure, and reducing the economic burden of the outbreak management. Subtyping allows discrimination between bacterial isolates of the same species (such as Escherichia coli isolates), to see if they are clones from the same source.
But diagnostic laboratories know that after many growth cycle in vitro, a bacterial strain can have small changes in their DNA after as few as 1 generation of bacterial cell division. Therefore, diagnosticians need experimental data to know what the expected mutation rate is for clonal isolates know if a new isolates are just slightly mutated daughter cells from the same ancestral mother, or if they are entirely different strains.
Several molecular diagnostic techniques are used to subtype bacterial strains, but the decreasing cost of whole genome sequencing (WGS) has increased its availability in diagnostic labs, and has allowed this more precise technique to replace the previous ones. The resolution and discrimination offered by WGS is significantly higher; it allows the detection of changes in individual nucleotides throughout the whole genome. Previous work demonstrated that WGS can be used for food outbreak source tracking, but it was unclear how different strains must be to be considered different. The rate at which common foodborne bacteria, such as Escherichia coli, Salmonella enterica ser. Thypimurium, Listeria monocytogenes, and Vibrio parahaemolyticus, change at the level of single nucleotides was not known.
In this study, cultures of 23 strains of Shiga toxin-producing E. coli, S. enterica ser. Thypimurium, L. monocytogenes, and V. parahaemolyticus were sub-cultured daily for 100 successive days. A team from McGill University, Health Canada and expert in the BioNumerics software from BioMérieux, lead by Professor Jennifer Ronholm a researcher of the CRIPA-FTQNT, measured and compared the whole genome sequences from the first culture and the last subculture (100th) of all the 23 strains to investigate how different they had become at the nucleotide level during these 100 days.
The genomes did not significantly change in size during sub-culturing, and no loss of genetic mobile element such as plasmids were observed. The number of Single Nucleotide Polymorphisms (SNPs) identified between the 1st and final subcultures varied between bacterial species and strains of the same species. The SNPs tended to occur in clusters in specific region of the bacterial genome and a highest number of SNPs detected for S. enterica ser. Typhimurium, then to a lesser extent for E. coli, V. parahaemoyticus and the least for L. monocytogenes. The number of allelic variants identified varied from 1 to 8 alleles in E. coli, 0 to 2 alleles in L. monocytogenes, 0 to 3 alleles in S. enterica. Which is in agreement with similar analysis performed on epidemiologically characterized isolates from recorded outbreaks. This allelic exchange analysis could not be performed for V. parahaemolyticus.
Therefore, the dataset of this study can be used as a reference to discriminate related isolate for E. coli, Listeria, Salmonella or Vibrio with WGS and epidemiological analysis in a food outbreak investigation. Future work could focus on developing a similar approach for other bacterial pathogens such as Campylobacter, for viral source tracking, or for understanding if these bacteria have more or less accumulated mutations in different growth matrices – for example, instead of lab media do bacteria change faster or slower when growing in ground meat.
This dataset, obtained from pure culture, does not represent what would occur in real infections or in food products. It is important to keep in mind that the time it takes for genomic substitutions to accumulate in laboratory mutation experiments will not necessarily reflect what is occurring in complex environments. For example, although the generation time for E. coli in pure culture can be as little as 20 min, this increases to approximately 24 h in the human gut, meaning there are fewer replication cycles and genomic changes will accumulate less rapidly in a real multi-microbial environment.
Source: Changes detected in the genome sequences of Escherichia coli, Listeria monocytogenes, Vibrio parahaemolyticus, and Salmonella enterica after serial subculturing. Can. J. Microbiol. 65: 842–850 (2019). Nicholas Petronella, Palni Kundra, Olivia Auclair, Karine Hebert, Mary Rao, Kyle Kingsley, Katrien De Bruyne, Swapan Banerjee, Alexander Gill, Franco Pagotto, Sandeep Tamber, and Jennifer Ronholm
