Canadian journal of microbiology最新文献

Declining costs of sequencing technology have catalyzed the widespread use of high-dimensional complex omics datasets in microbiology. While rich in information, these datasets present major analytical challenges, including sparsity, heterogeneity, and the need for robust statistical validation. Concerns about the reproducibility of findings across microbiological studies underscore the importance of standardized, transparent analytical approaches. Despite the availability of diverse statistical frameworks and machine learning methods, designing an appropriate statistical workflow (from method selection to model evaluation) remains challenging, particularly for researchers with limited advanced statistical training. Missteps in this process can lead to misinterpretation, irreproducibility, and flawed conclusions. This paper provides a structured, step-by-step framework to guide and validate the methodology of choosing the right statistical methods for both explanatory and predictive modeling in microbiology and translational research. We outline essential decision points spanning data preprocessing, feature selection, model assumptions, and model evaluation, and highlight common trade-offs and practical considerations. To demonstrate the guide's utility, we analyze a real-world COVID-19 dataset to identify cytokine biomarkers associated with disease severity. By aligning analytical strategies with microbiology inquiry, this guide aims to enhance reproducibility, empower data-informed decisions, and promote more rigorous, interpretable research in microbiology and public health.

Lake Guamuez is the second largest lake in Colombia and economically supports hundreds of families in the area. The main activities carried out in the region have focused on tourism, agriculture, livestock, and rainbow trout production; however, these activities have been associated with contamination of the lake. This research aimed to evaluate the water quality of Lake Guamuez using somatic coliphages (SCs) as bioindicators. For this purpose, periodic sampling was carried out for 6 months at nine strategic points of the lake. For the detection of SCs, the method described in 9211 D of the Standard Methods for the Examination of Water and Wastewater was used. The genomic variability and presence of virulence genes in the isolated SCs were determined. Water contamination in the lake is evident, and the SCs titer is greater in areas with a high flow of anthropogenic activities. An important degree of genetic diversity and a high prevalence of virulence genes could be observed among the SCs analyzed. The results when compared with guidelines and water quality standards from various countries showed concentrations of SCs higher than those allowed. The high prevalence of gastrointestinal diseases in the region suggests a link to water contamination.

Leptographium wingfieldii is a fungal associate of Tomicus piniperda (the pine shoot beetle) and pathogen of pines and this species is an agent of blue stain in sapwood on infected trees. This fungus was first reported from Europe and has been recently introduced to Canadian forests. Ten new mitogenomes have been sequenced and characterized, including seven strains of L. wingfieldii, two strains of L. procerum and one strain of L. terebrantis. The data were combined with other members of the Ophiostomatales collected from NCBI to gain more insight into the genetic diversity, evolution, and systematics of these fungi. The size of the studied mitogenomes of Leptographium species ranged from 41 to 126 kb with the number of potential mobile introns embedded within these mitogenomes ranging from 13 to 45. These data show that introns generate genetic diversity and confirms the contribution of mobile introns in genome expansion in Ophiostomatales fungi. This study also uncovered complex intron arrangements (twintrons) suggesting the potential of mobile introns generating complex ribozymes that may have implications in gene regulation.

Petroleum-associated water harbors diverse microbial communities, including hydrocarbon-degrading bacteria, sulfate-reducing bacteria, and methanogenic archaea. The growth and metabolism of these organisms, as well as their community composition, can affect various aspects of oil field development and oil produced water treatment. In this study, Illumina-based 16S rRNA gene sequencing was used to analyze the microbial community structures of oilfield produced water processed at two treatment stations and subjected to different treatment protocols. Significant differences in microbial community α-diversity and richness resulted from the different treatment protocols. The treatment of oil produced water effectively reduced the oil content, accompanied by the a reduction in Desulfobacterota. Proteobacteria was the dominant phylum in oil produced water; its core presence, along with Patescibacteria and Desulfobacterota, was identified in a co-occurrence network analysis of the microbial community. Redundancy analysis showed significant positive correlations between microbial community diversity and the oil and suspended solids contents of the oil produced water, highlighting the role of treatment protocols in shaping both microbial composition and water characteristics. Thus, this study provides potential insights into the processes of souring in oil fields and contributes to the theoretical understanding of oil-produced water treatment, which may inform future optimization of treatment protocols.

Iron is an essential mineral for almost all pathogenic bacteria, including Salmonella enterica serovar Typhimurium and Enteritidis. We have investigated the effect of the deletion of iroN, fepA, and fhu genes on the transcriptomic profiles of S. Typhimurium and S. Enteritidis strains with double (ΔiroNΔfepA) and triple (ΔfhuΔiroNΔfepA) gene deletions and grown under iron-deficient conditions. Significant changes were observed in the expression of genes involved in virulence, stress-response, and energy metabolism in both Salmonella serovars. The pathways most affected were the tricarboxylic acid cycle, electron transport chain, and stress responses all of which were downregulated while cysteine biosynthesis was upregulated. In general, common and/or related genes were affected in the double and triple mutant strains which indicated that the additional deletion of the fhu gene affected a limited number of genes, although S. Typhimurium showed more differences than S. Enteritidis. Nevertheless, the main difference observed between the mutants of the two serovars grown under iron-depleted conditions is the enhanced upregulation of the flagellum genes in S. Enteritidis. This study reveals evidence of novel interactions between metabolic pathways and virulence under iron limitation, providing insights into adaptive strategies that may contribute to the enhanced virulence of these Salmonella serovars.

The genus Trichoderma comprises many common fungi species that are distributed across the ecosystems. Trichoderma species have been successfully used as biofungicides due to their ability to protect plants and produce secondary metabolites (SMs) such as peptaibols, butenolides, pyridines, koninginins, and polyketide compounds. These SMs possess antimicrobial properties that allow the microbe to suppress or eliminate other pathogens, enabling it to secure a competitive nutritional niche. These SMs function as key agents in biocontrol strategies, contributing to crop protection and plant growth promotion, and are increasingly utilized in the development of bio-fertilizers. Trichoderma functions through multiple mechanisms that support plant health by inducing systemic resistance and by activating plant defense pathways. This article aims to review the bioactivity of selected Trichoderma-derived SMs with an emphasis on their beneficial effects, growth promoting attributes, and their effects on fungal prey. Additionally, the article provides a comprehensive overview of SMs in promoting sustainable agriculture and biological control.

Africa's vast geographic and climatic diversity makes it a critical region for the ecology and spread of avian influenza viruses, particularly due to its role as a wintering ground for Palearctic migratory waterbirds. The continent has experienced multiple waves of clade 2.3.4.4b A/H5Nx high pathogenicity avian influenza (HPAI), which has caused widespread outbreaks in poultry and wild birds since 2017. From 2023 to mid-2025, clade 2.3.4.4b A/H5N1 outbreaks were reported across West and Southern Africa, with severe impacts on poultry production and conservation of endangered wild bird species. Concurrently, South Africa and Mozambique battled an unprecedented A/H7N6 HPAI epizootic in 2023, leading to the culling or loss of over 6.8 million chickens. Additionally, the A/H9N2 subtype, particularly G5.5 sublineage strains, continues to circulate in North, West, and East Africa, with reassortant viruses with A/H5Nx viruses reported in Egypt. Underreporting and limited surveillance hamper accurate epidemiological assessment. Despite these challenges, advancements in noninvasive environmental sampling offer promising tools for early detection. Strengthening regional cooperation and surveillance is essential for mitigating future outbreaks and protecting both animal and public health.

Coinfection and secondary infection by fungi in patients with viral pulmonary infection, especially SARS-CoV-2, are important factors that worsen the prognosis and are associated to increased death rates. This work aims to report the prevalence of Candida isolates in bronchoalveolar and nasopharyngeal samples from suspected COVID-19 patients in the first-second pandemic waves and their antifungal resistance profile. From 2321 patients, 29.04% were diagnosed with SARS-CoV-2 infection. The yeast isolation rate of 6.97% (47/674) from positive SARS-CoV-2 was statistically higher than 4.43% (73/1647) from negative SARS-CoV-2 patients (p = 0.0177). Among yeasts, the most prevalent species was Candida albicans (63/120), with four being azole-resistant isolates (6.35%); however, other emerging and less susceptible species were also isolated, such as Candida guilliermondii (11), Candida glabrata (5), Candida lusitaniae (4), Candida krusei (1), and Candida norvegensis (1). Here, we highlighted Candida prevalence in respiratory tract, emphasizing the relevance for surveillance in SARS-CoV-2/COVID patients for improvement of management as well as patient outcomes.

Community-associated Clostridioides difficile infections (CA-CDI) remain a concern in Canada, comprising a quarter of cases previously reported through the Canadian Nosocomial Infection Surveillance Program. Previous Canadian studies have reported toxigenic C. difficile isolated from Canadian retail meat, suggesting that it may be a source of exposure for CA-CDI in Canada. In this study, 3/219 (1.4%) of retail pork and 0/99 (0%) of retail beef samples tested positive for toxigenic C. difficile, which were molecularly characterized by PCR ribotyping and whole-genome sequencing. All three isolates were obtained from pork and belonged to sequence types (STs)/ribotypes (RTs) that have previously been isolated from human clinical CA-CDI cases in Canada: ST1/RT027, ST8/RT002, and ST10/RT015. Retail meat isolates were susceptible to the antimicrobials tested, save one isolate with intermediate resistance to clindamycin. Genomic comparison to Canadian human clinical CA-CDI isolates with the same corresponding ST/RT types showed two of the three pork isolates clustered with CA-CDI isolates via core-genome multilocus sequencing typing, with single nucleotide variant (SNV) analysis showing further genomic relatedness of 2-11 SNVs. Retail meat may therefore be a low source of CA-CDI exposure in Canada, with the potential for foodborne transmission of select clones.