Canadian journal of microbiology最新文献

Antimicrobial resistance has a negative impact on people's health and the economy. New resistance mechanisms are emerging, making the treatment of infections very challenging. Fungi are well known for their production of secondary metabolites during active cell growth. In this study, a strain of Penicillium sanguifluum (111-12) was isolated from Manitoba soil and investigated for antimicrobial properties of fungal secondary metabolites against pathogenic bacteria, and two fungal plant pathogens that are known for causing Dutch elm diseases and chestnut blight disease. Penicillium sanguifluum (111-12) produced dehydrocurvularin (C1) and 11-hydroxycurvularin (C2). C1 and C2 were examined for their antimicrobial properties and these compounds were combined with various antibiotics to evaluate their potentiation (adjuvant) properties. Promising results were obtained for C1 that decreased the minimum inhibitory concentrations of cefepime, ceftazidime, tobramycin, and amikacin against a clinical multidrug resistant strain of Pseudomonas aeruginosa (PA82). In addition, C1 and C2 showed no impact on the Galleria mellonella model regarding toxicity.

Fusarium head blight (FHB) is a devastating fungal disease caused by Fusarium graminearum, which affects barley (Hordeum vulgare L.) and other small cereal grains. Fungal endophytes are microorganisms that reside inside tissues and considered that they may have been involved in various roles of the plants. This study involved the comparison of fungal endophytes between "non-infected/clean" and "FHB-infected" barley genotypes in various tissues collected at different plant developmental stages and were grown under different conditions (i.e., greenhouse, research field, and FHB-field nursery). We hypothesized that fungal endophytes diversity and abundance may differ between plant tissues in various barley genotypes that were non-infected and FHB-infected. The 18S-internal transcribed spacer sequencing analysis revealed a greater number of fungal operational taxonomic units (OTUs) and endophyte species in FHB-infected barley compared to clean barley. A one-way ANOVA and Tukey's pairwise comparison test (p ≤ 0.05) were performed to test significant differences. Higher seed endophyte diversity was found in FHB-infected (120 OTUs) compared to non-infected (113 OTUs) harvested in 2021. The increase in diversity of endophytes that contributes to different roles in plant protection and defense, such as biocontrol agents, may prevent the growth of Fusarium species and decrease FHB-infection.

Superficial fungal infections, mainly caused by dermatophytes, are a global public health issue. We evaluated the antifungal activity of six β-amino-ketones against Trichophyton rubrum, a leading agent of superficial mycoses. Among them, 3-(morpholin-4-yl)-1-phenylpropan-1-one (AB1) showed the most potent effect, with a minimum inhibitory concentration (MIC) of 7.81 µg/mL against the T. rubrum reference strain and fungicidal activity against clinical isolates, as demonstrated by minimum fungicidal concentration assays. AB1 was effective against both conidia and hyphae of T. rubrum, while showing limited activity against Candida albicans and the bacteria Escherichia coli and Staphylococcus aureus. Mechanistic studies suggest AB1 targets the fungal plasma membrane, possibly via ergosterol interactions, supported by increased MICs in ergosterol-rich conditions and membrane integrity assays. Confocal microscopy revealed morphological alterations in AB1-treated hyphae, indicative of membrane damage. Transmission electron microscopy confirmed cytoplasmic disorganization and membrane disruption at subinhibitory concentrations. Toxicological assays showed moderate cytotoxicity in human fibroblasts (IC₅₀ = 37.75 µg/mL) and no toxicity in Galleria mellonella larvae at high doses. These findings highlight AB1 as a promising antifungal candidate against Trichophyton spp., with the potential benefit of reduced impact on the host microbiota compared to broad-spectrum antimicrobials.

The One Health (OH) approach recognizes the interconnectedness of the health of people, animals, plants/crops and ecosystems, and is central to addressing antimicrobial resistance (AMR). The 7th Environmental Dimension of Antimicrobial Resistance Conference (EDAR7), held in Montreal in May 2024, exemplified this approach by convening international experts and stakeholders to discuss AMR research and policy progress. EDAR7 workshop #8 focused on (1) barriers to establishing effective OH AMR research programs, (2) gaps in OH AMR research priorities, and (3) potential solutions/approaches or "tools" to ensure programs develop in accordance with OH principles and generate insightful data that maximizes limited resources. Key workshop outcomes included identifying critical principles for OH AMR research programs and highlighting the pivotal role of sustainable data management strategies. Additionally, the importance of considering AMR policy and risk assessment needs when planning and designing research was emphasized. Discussions explored specific tools and approaches that support the standardized and harmonized collection and analysis of data, and associated challenges of integrating genomics data into current risk assessments and models. Synthesis of the workshop's discussions outlined critical considerations that interdisciplinary OH AMR research programs and networks should prioritize to enhance the impact of their outputs.

Salmonella enterica is a major foodborne pathogen capable of surviving in low-water-activity (a_W) foods and retaining the ability to invade intestinal epithelial cells after environmental stress, such as exposure to high salt concentrations. Although multiple serotypes tolerate low a_W, Tennessee strains have been repeatedly linked to outbreaks in dry foods, suggesting specific adaptations. This study evaluated the effects of NaCl (1%, 4%, and 6%) on growth, biofilm formation, post-biofilm recovery, and internalization capacity (Caco-2 cell assays) of six S. enterica strains-four Tennessee and two serogroup B isolates-from peanuts, raisins, chocolate, and dehydrated tomatoes. Growth and biofilm formation were monitored over a 7-day exposure to NaCl; post-biofilm recovery and internalization were assessed afterward. While all strains showed reduced internalization after salt exposure, Tennessee isolates generally maintained higher growth and biofilm formation than the ATCC 14028 reference strain. Phenotypic responses varied by strain and NaCl concentration, indicating differences in osmotic stress adaptation. The persistence of internalization capacity, even at reduced levels, highlights a potential food safety risk in NaCl-preserved products. These findings emphasize the need to consider strain-specific traits when developing control measures for Salmonella in dry food environments.

Highlights: Cannabidiol (CBD) decreases the growth of C. albicans. CBD inhibits the yeast-to-hyphae transition. CBD reduces biofilm formation by C. albicans. CBD induces C. albicans death through necrosis.

Acinetobacter baumannii is an opportunistic pathogen that is often studied in commonly used rich media in laboratories worldwide. Due to the metabolic versatility of A. baumannii, it can be cultured in different growth mediums; however, this can lead to genotypic and phenotypic variations. In this study, we compared phenotypic and transcriptomic changes in A. baumannii ATCC17978-VU cultured in M9 minimal media supplemented with 20 mmol/L sodium succinate and rich lysogeny broth media. Phenotypically, growth was significantly slowed, virulence in Galleria mellonella was attenuated, and susceptibility to a variety of antibiotic classes was reduced when A. baumannii ATCC17978-VU was grown in minimal media versus rich media. Transcriptomic analysis showed differential regulation of >700 genes-including those associated with energy production and ribosomal function-when the two growth conditions were compared, with the majority of the upregulated genes seen in minimal media of unknown function. This study showed that culture media has a profound effect on the phenotype and cellular workings of a bacteria, highlighting the need for more studies of pathogens like A. baumannii ATCC17978-VU in minimal media.

Climate change is rapidly altering Arctic marine environments, leading to warmer waters, increased river discharge, and accelerated sea ice melt. The Hudson Bay Marine System experiences the fastest rate of sea ice loss in the Canadian North resulting in a prolonged open water season during the summer months. We examined microbial communities in the Hudson Strait using high throughput 16s rRNA gene sequencing during the peak of summer, in which the bay was almost completely ice-free, and air temperatures were high. We found that salinity and temperature significantly affected the taxonomic composition among microbial communities across sites. We observed a higher relative abundance of specific Polaribacter sp. Amplicon sequence variants (ASVs) at more saline sites. Shannon diversity was not significantly impacted by salinity or temperature. These results contribute to our understanding of surface water microbial community composition in the Hudson Strait and shed light on how future salinity and temperature conditions may favour certain microbial populations.

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.