Bacterial microbiota shifts in vacuum-packed beef during storage at different temperatures: Impacts on blown pack spoilage.

We aimed to evaluate the bacterial growth and diversity in vacuum-packed beef bags stored at different temperatures and to monitor blown-pack spoilage. We used culture-based methods and high-throughput sequencing to study the development of the main bacterial groups naturally present in beef stored at 4 and 15 °C for 28 days. The growth of sulfite-reducing clostridium (SRC) was impaired in beef bags stored at 4 °C; significant differences among SRC counts were observed in beef bags stored at 4 and 15 °C on days 14, 21, and 28 (P = 0.001). Blown pack was observed in most beef bags stored at 15 °C, from day 14 to day 28, but not in beef bags stored at 4 °C. A storage temperature of 4 °C was able to maintain a stable bacterial microbiota (most prevalent: Photobacterium, Hafnia-Obesumbacterium, and Lactococcus). Remarkable changes in microbial abundance occurred at 15 °C from day 14 to day 28, with a predominance of strict anaerobes (Bacteroides) and the presence of Clostridium spp. The relative frequencies of strict anaerobes and Clostridium were statistically higher in the beef bags stored at 15 °C (P < 0.001 and P = 0.004, respectively). The temperature influenced the microbial counts and relative abundance of spoilage bacteria, leading to blown pack spoilage.

Metataxonomics contributes to unravel the microbiota of a Brazilian dairy.

For this research communication, 90 samples of a Brazilian dairy were combined into four groups (raw material, final product, food-contact and non-food contact surfaces) and analyzed by metataxonomics based on 16S rRNA gene sequencing. The results showed high alpha-diversity indexes for final product and non-food contact surfaces but, overall, beta-diversity indexes were low. The samples were separated in two main clusters, and the core microbiota was composed by Macrococcus, Alkaliphilus, Vagococcus, Lactobacillus, Marinilactibacillus, Streptococcus, Lysinibacillus, Staphylococcus, Clostridium, Halomonas, Lactococcus, Enterococcus, Bacillus and Psychrobacter. These results highlight that rare taxa occur in dairies, and this may aid the development of strategies for food protection.

Harnessing Machine Learning to Uncover Hidden Patterns in Azole-Resistant CYP51/ERG11 Proteins.

Fungal resistance is a public health concern due to the limited availability of antifungal resources and the complexities associated with treating persistent fungal infections. Azoles are thus far the primary line of defense against fungi. Specifically, azoles inhibit the conversion of lanosterol to ergosterol, producing defective sterols and impairing fluidity in fungal plasmatic membranes. Studies on azole resistance have emphasized specific point mutations in CYP51/ERG11 proteins linked to resistance. Although very insightful, the traditional approach to studying azole resistance is time-consuming and prone to errors during meticulous alignment evaluation. It relies on a reference-based method using a specific protein sequence obtained from a wild-type (WT) phenotype. Therefore, this study introduces a machine learning (ML)-based approach utilizing molecular descriptors representing the physiochemical attributes of CYP51/ERG11 protein isoforms. This approach aims to unravel hidden patterns associated with azole resistance. The results highlight that descriptors related to amino acid composition and their combination of hydrophobicity and hydrophilicity effectively explain the slight differences between the resistant non-wild-type (NWT) and WT (nonresistant) protein sequences. This study underscores the potential of ML to unravel nuanced patterns in CYP51/ERG11 sequences, providing valuable molecular signatures that could inform future endeavors in drug development and computational screening of resistant and nonresistant fungal lineages.

Profiling the Bacterial Community of Fermenting Traminette Grapes during Wine Production using Metagenomic Amplicon Sequencing.

Advances in sequencing technology and the relatively easy access to the use of bioinformatics tools to profile microbial community structures have facilitated a better understanding of both culturable and non-culturable microbes in grapes and wine. During industrial fermentation, microbes, known and unknown, are often responsible for product development and off-flavor. Therefore, profiling the bacteria from grape to wine can enable an easy understanding of in situ microbial dynamics. In this study, the bacteria of Traminette grapes must undergoing fermentation, and the final wine were subjected to DNA extraction that yielded 15 ng/µL to 87 ng/µL. The 16S amplicon of the hypervariable region of the V4 region was sequenced, relatively abundant bacteria consisting of phyla Proteobacteria, Actinobacteriota, Firmicutes, Bacteroidota, Fusobacteriota and followed by the Verrucomicrobiota, Halobacterota, Desulfobacterota, Myxococcota, and Acidobacteriota. A Venn diagram analysis of the shared unique operational taxonomic units (OTU) revealed that 15 bacteria phyla were common to both grape must, fermenting stage, and final wine. Phyla that were not previously reported were detected using the 16S amplicon sequencing, as well as genera such as Enterobacteriaceae and Lactobacillaceae. Variation in the organic nutrient use in wine and its impact on bacteria was tested; Traminette R tank containing Fermaid O and Traminette L stimulated with Stimula Sauvignon blanc + Fermaid O. Alpha diversity using the Kruskal-Wallis test determined the degree of evenness. The beta diversity indicated a shift in the bacteria at the fermentation stage for the two treatments, and the final wine bacteria looked similar. The study confirmed that 16S amplicon sequencing can be used to monitor bacteria changes during wine production to support quality and better utilization of grape bacteria during wine production.

A set of antibiotic-resistance mechanisms and virulence factors in GES-16-producing Klebsiella quasipneumoniae subsp. similipneumoniae from hospital wastewater revealed by whole-genome sequencing.

Klebsiella quasipneumoniae subsp. similipneumoniae has emerged as a human pathogen and sporadic isolates from non-clinical sources were reported. Here, we described the phenotypic- and genomic-characteristics of a multidrug-resistant (MDR) and potentially hypervirulent (MDR-hv) Klebsiella quasipneumoniae subsp. similipneumoniae (KqA1) isolated from hospital wastewater. The antibiotic susceptibility profile of KqA1 was investigated using disk-diffusion method, broth microdilution method, and agar dilution method, and the genetic characteristics of antimicrobial resistance, mobile genetics elements, and virulence were evaluated by genomic DNA sequencing on the Illumina® NovaSeq6000 platform as well as by bioinformatic analysis. Resistome analyses revealed the presence of genes related to resistance to ß-lactams, aminoglycosides, quinolones, tetracyclines, sulfonamides, trimethoprim, chloramphenicol, macrolides, and fosfomycin. New genetic contexts to blaGES-16 (carbapenemase gene) and to fosA (fosfomycin resistance gene) were described. A set of mechanisms that can contribute to antibiotic resistance, commonly detected in Klebsiella spp., was also found including chromosomal mutations, efflux systems, proteins, and regulators. Moreover, KqA1 presented genes related to tolerance to metals (arsenic, copper, nickel, cobalt, magnesium, cadmium, zinc, tellurium, selenium) and to biocides (quaternary-ammonium compounds). The isolate was classified as potentially hypervirulent due to a wide range of virulence factors found associated to regulation, motility, biofilm, effector delivery systems, immune modulation, nutritional/metabolic factors, adherence, invasion, and competitive advantage. The occurrence of MDR-hv KqA1 in hospital wastewater points out how this environment matrix plays a crucial role in the maintenance and selection of critical bacterial pathogens. Regarding One Health perspective, it is evident the need for multidisciplinary implementation of control measures for antibiotic-resistant bacteria, not only in hospital settings but also in a general environmental context to mitigate the dissemination of MDR and hv bacteria.

Comparative phylo-pangenomics reveals generalist lifestyles in representative Acinetobacter species and proposes candidate gene markers for species identification.

Acinetobacter species have the potential to invade and colonize immunocompromised patients, therefore being well-known as opportunistic pathogens. Among these bacteria, the species of the Acinetobacter calcoaceticus-Acinetobacter baumannii "complex" (Acb members) emerge as the main often isolated bacteria in clinical specimens. The unequivocal taxonomy is crucial to correctly identify these species and associated with comparative genomic analyses aids to understand their life-styles as well. In this study, all publicly available Acinetobacter species at the date of this study preparation were analyzed. The results revealed that the Acb members are in fact a complex when phenotypic methods are confronted, while for comparative and phylogenomics analyses this term is misleading, since they composed a monophyletic group instead. Nine best gene markers (response regulator, recJ, recG, phosphomannomutase, pepSY, monovalent cation/H + antiporter subunit D, mnmE, glnE, and bamA) were selected for identification of Acinetobacter species. Moreover, representative strains of each species were split according their isolation sources in the categories: environmental, human, insect and non-human vertebrate. Neither niche-specific genome signature nor niche-associated functional and pathogenic potential were associated with their isolation source, meaning it is not the main force acting on Acinetobacter adaptation in a given niche and corroborating that their ubiquitous distribution is a reflex of their generalist life-styles.