Determining genotype and antimicrobial resistance of Salmonella Typhi in environmental samples by amplicon sequencing

Estimates of the burden of typhoid fever due to Salmonella enterica serovar Typhi (S. Typhi) rely on data from clinical surveillance, which is rarely done in low income settings and is also limited by the poor sensitivity of the assays used and the reliance on health seeking by patients. Environmental surveillance for S. Typhi shed by symptomatic and asymptomatic individuals in wastewater offers a sensitive surveillance tool that could help to inform burden estimates. Sequencing S. Typhi direct from wastewater concentrates has the potential to identify circulating genotypes and associated antimicrobial resistance (AMR) genes, supporting public health interventions such as vaccination and antimicrobial usage.

We designed a multiplex targeted amplicon sequencing protocol for genotyping and determining AMR in S. Typhi from wastewater samples, targeting SNPs that identify genotypes of interest and both chromosomal and plasmid-borne AMR. PCR products were sequenced using the Oxford Nanopore Technologies (ONT) MinION, and genotypes and AMR identified using the GenoTyphi program. We tested this approach on samples from south India from both hospital outflow and wastewater collected from the community. All samples tested were suspected to be positive for S. Typhi following quantitative PCR for ttr, tviB, and staG gene targets. Out of 110 samples tested we were able to determine a genotype and/or AMR for 8. All samples that gave a genotype call suggested a genotype consistent with those found in clinical cases in India during the same time period and produced consensus sequences that clustered with S. Typhi when included in a phylogenetic tree.

In this study, we provide proof of concept data for amplicon sequencing of S. Typhi in wastewater which with further optimisation could be used to complement clinical surveillance data or provide data on S. Typhi presence in the absence of clinical surveillance. This information can inform public health interventions, and the concept could be applied to other pathogens of interest for genotyping from environmental surveillance samples.