Nanopore-based pathogen surveillance allows complete metagenome-assembled genome reconstruction of low-abundance enteric pathogens in wastewater samples
Gauthier, J.; Mohammadi, S.; Kukavica-Ibrulj, I.; Boyle, B.; Landgraff, C.; Goodridge, L.; Levesque, R. C.
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BackgroundPathogen surveillance often relies on culture-based methods and epidemiological traceback investigations that are both time- and cost-ineffective, especially in the case of enteropathogenic bacteria contaminating food supplies. Nevertheless, metagenomic sequencing of wastewater influent helps conduct continuous, culture-independent, and community-level monitoring of microbes shed from the human gut microbiome. However, even though amplicon-based microbiome census methods help identify taxa, they typically do not allow strain-level epidemiology or investigating virulence factors and antimicrobial resistance mechanisms involved in an outbreak. Conversely, whole metagenome shotgun sequencing allows both taxonomic surveys and genome reconstruction. ResultsHere we present a metagenomic "tracking and assembling" workflow, applied between September 2023 to January 2024, in which we tracked two low-abundance enteric pathogens (Shiga toxin-producing Escherichia coli and enteropathogenic non-typhoidal Salmonella enterica; 0.1-1% total reads) and reconstructed 95-99% complete genomes using a combined taxonomic read binning and reference-based assembly. Furthermore, for these two pathogens, a maximum abundance peak significantly above baseline levels, assuming 95% confidence, was detected and found to precede by a month two public food recalls, all within the same urban community where municipal wastewater sampling was conducted (Quebec City, Canada). ConclusionsThis present work suggests that a continuous "tracking and assembling" approach enhances the resolution of low-abundance pathogen monitoring to the strain level, while also providing information about the gene contents of low-abundance enteropathogens, even when relative abundance is too low to reconstruct genomes via a generic de novo assembly and contig binning approach.
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