Evaluation of multiplex nanopore sequencing for Salmonella serotype prediction and antimicrobial resistance gene and virulence gene detection - Wu, Xingwen; Luo, Hao; Ge, Chongtao; Xu, Feng; Deng, Xiangyu; Wiedmann, Martin; Baker, Robert C.; Stevenson, Abigail E.; Zhang, Guangtao; Tang, Silin (Frontiers in Microbiology, 2023)
In a previous study, Multiplex-nanopore-sequencing based whole genome sequencing (WGS) allowed for accurate in silico serotype prediction of Salmonella within one day for five multiplexed isolates, using both SISTR and SeqSero2. Since only ten serotypes were tested in our previous study, the conclusions above were yet to be validated in a larger scale test. In the current study we validated this workflow with 69 Salmonella serotypes and also explored the feasibility of using multiplex-nanopore-sequencing based WGS for antimicrobial resistance gene (AMR) and virulence gene detection. We found that accurate in silico serotype prediction with nanopore-WGS data was achieved within about five hours of sequencing at a minimum of 30 × Salmonella genome coverage, with SeqSero2 as the serotype prediction tool. For each tested isolate, small variations were observed between the AMR/virulence gene profiles from the Illumina and Nanopore sequencing platforms. Taking results generated using Illumina data as the benchmark, the average precision value per isolate was 0.99 for both AMR and virulence gene detection. We found that the resistance gene identifier - RGI identified resistance genes with nanopore data at a much lower accuracy compared to Abricate, possibly due to RGI’s less stringent minimum similarity and coverage by default for database matching. This study is an evaluation of multiplex-nanopore-sequencing based WGS as a cost-efficient and rapid Salmonella classification method, and a starting point for future validation and verification of using it as a resistance/virulence gene profiling tool for the food industry. This study paves the way for the application of nanopore sequencing in surveillance, tracking, and risk assessment of Salmonella across the food supply chain.