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bioRxiv · 10.1101/2023.03.10.532158

High Resolution Salmonella Subtyping by the MLSTnext Method

Ma, Z.·Gharizadeh, B.·Huang, S.·Jia, M.·Wu, F.·Wang, C.
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Abstract

The food industry needs a straightforward, efficient, widely applicable and cost-efficient method to not only detect, but also determine serovar and potential sources of multiple strains in food and environment. While Whole Genome Sequencing (WGS) can generate complete genomic profile of food pathogens, it is a laborious, time-consuming, and expensive method that necessitates pure isolates. As a result, it is unsuitable for samples with complex background, limiting its widespread application by food industry. However, traditional multilocus sequence typing (MLST) approaches do not provide sufficient single nucleotide polymorphism (SNP) information to effectively track- and-trace sources of contamination. In contrast, ChapterDx MLSTnext-NGS (next-generation sequencing) Salmonella assay amplifies and sequences 47 polymorphic loci, evenly spanning the Salmonella enterica genome. As demonstrated in this study, the ChapterDx MLSTnext-NGS Salmonella can identify serovar with high resolution, distinguishing between various strains of the same serovar and resolve co-presence of different strains in a single sample. Additionally, this assay can analyze up to thousand samples in a single sequencing run within 22 hours, making it a highly efficient and scalable method for the food industry. Moreover, the cost per sample of the ChapterDx MLSTnext-NGS Salmonella assay is comparable to that of quantitative Polymerase Chain Reaction (qPCR), making it an affordable option. The assay uses ChapterDx amplification technology, allowing for the amplification of all 47 loci in a single-tube, single-step PCR reaction. This makes it one of the simplest NGS applications available. In summary, ChapterDx MLSTnext-NGS Salmonella assay can be implemented in many diagnostic laboratories to address increasingly complex food safety issues.

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Ma, Z., Gharizadeh, B., Huang, S., Jia, M., Wu, F., Wang, C.. 2023-03-11. High Resolution Salmonella Subtyping by the MLSTnext Method. https://doi.org/10.1101/2023.03.10.532158

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