Diagnostic testing of foot-and-mouth disease virus (FMDV) currently utilizes reverse transcription quantitative PCR (RT-qPCR) to detect the presence of viral RNA and double antibody sandwich ELISAs (DAS-ELISAs) to determine viral serotype. Serotype identification is critical to support informed vaccine selection to combat outbreaks. While DAS-ELISAs are capable of serotype identification, the test suffers from low sensitivity and requires a viral isolate for successful detection. In this study, we developed FMDV-ONTAPS: an Oxford Nanopore Technologies Amplicon P1 Sequencing protocol involving reverse transcription-PCR to amplify P1 of the FMDV genome, and Nanopore sequencing of the amplicons to provide genetic data for serotype and subtype/topotype identification. FMDV isolates representing all seven serotypes were successfully sequenced with this method. Additionally, the protocol successfully provided serotype identification from a variety of specimen matrices obtained from experimentally infected animals that included milk, serum, oral and nasal swabs, tissue suspensions, vesicular fluid, and oral fluid. The limit of detection for FMDV cell culture isolates was comparable for both sequencing and RT-qPCR detection. RT-qPCR Cq values for clinical samples evaluated ranged from 8 to 28.21. Sequencing was successful for all samples except for a single tissue suspension sample (Cq of 28.21). Identification of FMDV serotype in clinical samples is critical for effective outbreak response, and Nanopore sequencing offers a timelier and more sensitive alternative to DAS-ELISAs.

Despite the provision of a mumps vaccination program in Canada for over three decades, mumps has not reached elimination. Instead, a re-emergence has been observed in vaccinated populations, particularly in young adults. These outbreaks have been almost exclusively due to genotype G infections, a trend that has been seen in other countries with high mumps vaccination rates. To characterize mumps outbreaks in Canada, genomes from samples from Manitoba (n = 209), Newfoundland (n = 25), and Nova Scotia (n = 48) were sequenced and analysed by Bayesian inference. Whole genome sequencing was shown to be highly discriminatory for outbreak investigations compared to traditional Sanger sequencing. The results showed that mumps virus genotype G most likely circulated endemically in Canada and between Canada and the US. Overall, this Canadian outbreak data from different provinces and ancestral strains demonstrates the benefits of molecular genomic data to better characterize mumps outbreaks, but also suggests genomics could further our understanding of the reasons for potential immune escape of mumps genotype G and evolution in highly vaccinated populations. With a possible endemic circulation of mumps genotype G and the remaining risk of new imported cases, increased surveillance and alternative vaccination strategies may be required for Canada to reach the current target for mumps or a future elimination status.

Pathogen genomic surveillance is globally recognized as a pillar of public health. This field has expanded rapidly following the onset of the coronavirus disease 2019 (COVID-19) pandemic, and there is an urgent need to ensure the quality, comparability and reliability of the results of genomic analyses across diverse settings and analytical platforms. Currently, no methodology or framework has been universally adopted to mitigate this issue. This study aimed to provide a solution within the Canadian public health landscape by using standardized test datasets for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic analysis. In this context, a test dataset refers to a curated set of genomic sequences designed to evaluate the accuracy, consistency and performance of sequencing workflows, bioinformatics pipelines and analytical tools. These datasets serve as benchmarks, allowing laboratories to validate their methodologies and ensure comparability across different platforms. The test datasets included in this analysis were selected based on the use of well-characterized experimental protocols from the application of specimen selection criteria, through to sequence generation. Datasets generated using Illumina and Nanopore sequencing of samples from COVID-19 patients in Saskatchewan, Canada, were used and included clean controls, variable lineages and spiked-in lower-quality run data. Illumina libraries were sequenced using ARTIC network PCR amplification, while Nanopore libraries underwent similar protocols with some modifications. Public test dataset access on Zenodo further facilitates reproducibility, providing data summary outputs and pipeline environment files. A customized R script was developed to compare Illumina data, generating multiple tables and figures highlighting comparisons between analyses. The significance of this study lies in its contribution to the implementation of bioinformatic pipeline validation tools and protocols, which are essential for reliable genomic surveillance and outbreak response. By establishing a structured framework for computational validation, this study enhances the accuracy, comparability and efficiency of genomic surveillance in an evolving landscape of viral strains and testing strategies.