Canadian Food Inspection Agency

Staphylococcus shinii is a recently proposed staphylococcal species identified in animal-associated microbiomes and fermented foods, with promising probiotic and biotechnological applications. However, its genomic diversity, functional traits and safety profile need to be well established. Here, we report the first recovery and genome sequencing of 41 S. shinii isolates from blueberry fruit washes and surrounding air. Phylogenomic analysis, including reference genomes, revealed at least 15 well-supported intra-species lineages (genomovars) defined by phylogenetic relationship and average nucleotide identity (>99.5% within genomovars; <99.5% between them). Pangenome analysis showed a highly conserved core genome comprising 83.3% of genes, alongside diverse accessory genes across genomovars. Core functions in S. shinii included carbohydrate metabolism, vitamin biosynthesis and short-chain fatty acid production, traits potentially linked to probiotic properties. Biosynthetic gene clusters for bioactive compounds were broadly conserved, although genes encoding ribosomally synthesized and post-translationally modified peptides varied among genomovars. About 10-18 antimicrobial resistance genes (ARGs) were identified per S. shinii genome, several of which were located on the chromosome. Phenotypic testing confirmed susceptibility to ciprofloxacin, gentamicin and ampicillin, while resistance to other antimicrobials varied and was often plasmid-associated. Resistance patterns differed across genomovars, emphasizing the need for intra-species resolution in risk assessment. Although major virulence factors listed in the Virulence Factor Database were absent, putative pathogenicity-related genes were found in the core genome using the Pathogen-Host Interaction Database. Their presence, along with ARGs, underscores the need for caution in clinical contexts. Nonetheless, the absence of major virulence determinants and the presence of beneficial traits in some S. shinii isolates support their potential use in the agri-food system or environmental biotechnology, pending strain-specific safety evaluation.

Muskox (Ovibos moschatus, Zimmermann 1780), or Umingmak (in Inuktitut), is a critical component of the terrestrial Arctic ecosystem. In many regions, muskoxen are key to Inuit food security and important to cultural identity, while also providing economic opportunity. Although muskox populations in Greenland and part of Canada appear to be thriving, others are experiencing an uncertain future. A comprehensive understanding of factors driving demographic change, including Indigenous and western science-based knowledge of muskox biology and the Arctic ecosystem in which it lives, is necessary to safeguard populations in the crosshairs of climate change. The inclusion of genomic (or DNA-based) tools into management is predicated on Inuit needs and the amenability of such tools for co-development with Indigenous and scientific partners. The Muskox and Genomics in the Community (MAGIC) workshop was held in Cambridge Bay, Nunavut in January 2024, providing a cross-cultural grounding for discussion on the co-development of genomic tools for muskox conservation and management. Outcomes included forging opportunities for co-learning and knowledge exchange around genomics science and Inuit traditional ecological knowledge, identification of relevant species for whole genome sequencing, documentation of knowledge gaps in muskox biology, and laying conceptual foundations for the co-development of genomics tools based on Inuit Qaujimajatuqangit.

We present a comprehensive view of the human and animal domain perspectives, implications and significant considerations on M. tuberculosis complex variants adapted to animals, with the aim to highlight the areas of overlap in these fields and the need for a unified approach to tackling this problem. Expansion of molecular and genomic diagnostic methods has led to improved discrimination between M. tuberculosis complex variants, which illuminated the greater role in clinical and veterinary medicine of some previously under-recognized organisms (e.g. M. orygis). Similarly, genomic epidemiology has been used to untangle the intricate transmission networks of these organisms, spanning the animal-human interface. M. tuberculosis complex is a diverse group of organisms with members capable of infecting both human and animal hosts, with animal-adapted variants also equipped to cross species barriers. This complex group of organisms can cause a spectrum of disease manifestations, however, the extent of the burden of animal-adapted M. tuberculosis strains in human and animals hosts is not always well recognized, owing to such factors as difficulties with sample collections, siloed approaches and inter-jurisdictional complexities, as well as paucity and variability of available targeted diagnostic methods. We describe here the current perspectives on disease burden and clinical manifestations of different animal variants of M. tuberculosis complex in both animal and human hosts, as well as the diagnostic landscape available to detect and differentiate members of the complex. We highlight that coordinated One Health approaches with effective collaboration of all relevant stakeholders is needed to comprehensively and successfully address this problem for the betterment of both the human and the animal health.

Parasitic disease outbreaks remain a major challenge in aquaculture, and approved veterinary drugs needed for controlling such diseases are limited. Levamisole has emerged as a promising alternative in fish farming because of its anthelmintic and immunostimulant properties, although it has not yet been approved for use. This study aimed to evaluate, for the first time, the residue depletion (non-radiolabelled) profile of levamisole and estimate its withdrawal period in Nile tilapia (Oreochromis sp.) fish after oral administration under tropical conditions. Preliminary in vitro metabolism experiments supported the use of the parent compound as the marker residue. Levamisole was incorporated into medicated feed using an ethyl cellulose coating, resulting in uniform drug distribution (CV =10%) and low leaching (<5% in 15 min). Fish were treated with the drug at a daily dose of 30 mg kg(-1) of body weight for seven consecutive days. The average water temperature and pH were 30.2 degrees C and 7.3, respectively. Muscle and skin (in natural proportions) were collected at different times post-treatment for LC-MS/MS analysis. Residue levels detected were below 2 mu g kg(-1) at 120 h after the final dose. A withdrawal time of 97 degrees C-days, equivalent to 4 days, was estimated. This study offers key insights into the use of levamisole, including the proper incorporation into medicated feed to ensure effective dosing and minimize environmental contamination. The study addresses a critical gap by establishing a withdrawal period and supports practices that may promote food safety within the One Health approach.

In recent years, AI-driven platforms have transformed citizen science by collecting and generating valuable records of living organisms for monitoring biological data. Many applications utilize visual similarity and geospatial information to identify species based on photographs. This study investigates how location impacts plant identifications made by iNaturalist, particularly in detecting invasive alien plants (IAP) that are not established in an area. We also compare the accuracy of iNaturalist and PlantNet while exploring potential biases. To assess iNaturalist's taxonomic accuracy under varying location parameters, specimens of plants that are native and naturalized in Ontario, termed "established plants" for the purpose of this study, were collected and photographed (n = 61) and photographs of plants from Canada's regulated pest list, which are either not present or have a very limited distribution in Canada, termed "outsider plants" for the purpose of this study were exported from iNaturalist and GBIF (n = 402). We used photographs of the established plants to compare taxonomic accuracy between applications, considering factors such as plant families, distribution status, and visible parts. A scoring system was established, and a cumulative linked mixed model was applied to analyze taxonomic accuracy. Our findings reveal that restricting location significantly hinders iNaturalist's ability to identify IAP, highlighting the potential for missed detections. While sample size limitations prevented a robust comparison between applications, we also found significantly lower identification accuracy for species in the Poaceae family and for photographs featuring only leaves. Ultimately, recognizing the influence of location is essential for effectively monitoring IAP and leveraging iNaturalist as a tool for early detection.