The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform the public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN – VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). In addition, the portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. From inception to execution, the portal was developed with a conscientious focus on strong data governance principles and practices. Extensive efforts ensured a commitment to Canadian privacy laws, data security standards, and organizational processes. This portal has been coupled with other resources, such as Viral AI, and was further leveraged by the Coronavirus Variants Rapid Response Network (CoVaRR-Net) to produce a suite of continually updated analytical tools and notebooks. Here we highlight this portal (https://virusseq-dataportal.ca/), including its contextual data not available elsewhere, and the Duotang (https://covarr-net.github.io/duotang/duotang.html), a web platform that presents key genomic epidemiology and modelling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the portal (COVID-MVP, CoVizu), are all open source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.

We report the draft genome sequences of 25 Salmonella enterica strains representing 24 different serotypes, many of which were not available in public repositories during our selection process. These draft genomes will provide useful reference for the genetic variation between serotypes and aid in the development of molecular typing tools.

Background/Objectives: The diagnosis of Mycobacterium tuberculosis complex (MTBC) and nontuberculous mycobacterial (NTM) infections is accomplished by three main diagnostics methods: smear microscopy, culture, and molecular testing. Diagnostic algorithms used by laboratories can significantly impact clinical and infection control management. Current Canadian Tuberculosis Standards recommend the use of nucleic acid amplification testing (NAAT) for smear-positive patients and smear-negative patients upon request. An alternative algorithm is to utilize NAAT in the Panel approach on all samples, pulmonary and extrapulmonary, to potentially reduce time to diagnosis and treatment. This alternative approach was implemented in November 2019 at the Newfoundland and Labrador Public Health and Microbiology Laboratory (NL PHML) using a laboratory-developed multiplex real-time PCR (LDT m-qPCR) assay targeting Mycobacterium spp. (Myco spp.) and MTBC, performed in parallel with smear and culture. Methods: To investigate the impact of this alternate testing approach, we conducted an observational retrospective analysis of laboratory diagnostic and treatment data, recognizing that temporal changes in epidemiology, clinical practice, and laboratory workflow may also have influenced outcomes. To complete this, study data from three years before and four years after implementation were gathered. Results: The sensitivity/specificity of the smear, m-LDT qPCR-MTBC, m-LDT qPCR-Myco spp., and culture assays in this study were 18.1%/100%, 96.7%/99.8%, 47.6%/99.0%, and 96.8%/100%, respectively. The gold standard utilized for these calculations was clinical diagnosis for active MTBC disease and culture for NTM infections, recognizing that the use of clinical diagnosis may introduce subjectivity. The Panel approach reduced the time to diagnosis of tuberculosis MTBC by 29 days (p < 0.0001) for NL PHML, and when modelled for a laboratory with rapid culture identification, diagnosis was reduced by 14 days (p = 0.003). Among non-empirically treated tuberculosis patients, the time to treatment was decreased by 25.5 days (p < 0.001). For NTM infections, rapid diagnostics only affected one patient’s treatment. This finding agrees with clinical management guidelines, which do not routinely utilize rapid diagnostics for the diagnosis of disease or treatment decisions. The cost implications of additional NAAT testing were calculated to be an increase of CAD 23.62 per sample. Conclusions: Our findings support the adoption of a molecular assay for MTBC as an initial diagnostic tool to decrease time to diagnosis and time to treatment, depending on local epidemiology and irrespective of smear status. Utilizing a molecular assay for genus level identification of NTM had minimal impact on clinical management suggesting its limited diagnostic utility in a broad population setting.

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.

The incidence of tuberculosis disease (TBD) in New Brunswick (NB) is low but has been rising over the past decade. Analyzing these trends can help identify specific risk factors and transmission patterns to guide targeted public health strategies. This study aimed to provide a comprehensive and detailed characterization of TBD in NB by examining data from 1 January 2002, to 31 December 2024. All TB patients with Mycobacterium tuberculosis complex (MTBC) clinical isolates identified in NB healthcare facilities were eligible for inclusion in the study. We analyzed demographic, drug susceptibility, and 24-locus Mycobacterial Interspersed Repetitive Unit-Variable Number Tandem Repeat (MIRU-VNTR) data from 166 patients. Most MTBC isolates were pan-susceptible to first-line anti-tuberculosis drugs (90.9–98.1%), with 2.4% showing multidrug resistance. The MIRU-VNTR demonstrated a high discriminatory power of 0.9982 and a low clustering rate of 20.4%. Two samples from the same patient, collected seven years apart, showed different genetic profiles, suggesting that the second episode was a new infection. The most prevalent MTBC lineage was East African Indian (n = 23, 13%). This study provides early insights into TB trends in NB, including what may be the first recorded case of TB reinfection in NB. Our findings will help guide future TB research, policies, and public health interventions in the region.