Staphylococcus aureus is a causative agent of different infectious processes, food poisoning, and autoimmune disorders. The horizontal transfer of pathogenic strains can occur from animal to human under both house and farm conditions, and the spread of strains with antibiotic resistance is an existing problem. In addition to the spread of antibiotic-resistant strains in clinics, this problem also exists in veterinary medicine. It is especially important to monitor antibiotic resistance on farms where antibiotics are the standard treatment of animals, which may trigger the spread of antibiotic-resistant strains among animals and to the human population, and these strains can also be distributed in milk products produced by these farms (milk, cheese, and butter). In this work, we investigated 21 S. aureus isolates using whole-genome sequence analysis and tried to establish a relationship between these isolates with the development of bovine mastitis in seven regions of Western Russia. An S. aureus virulence profile was identified. We identified two groups of S. aureus associated with subclinical mastitis, namely, the enterotoxin-positive and enterotoxin-negative groups. The most prevalent factor associated with bovine mastitis in Russia was cytotoxins, including hemolysins and leukocidins. Multidrug resistance strains were investigated, and antibiotic resistance genes were identified. We identified S. aureus ST 97 type as the most common type in the regions in Western Russia. To the best of our knowledge, this is the first in-depth study of a range S. aureus isolates originating from cattle infections in Russia.
Summary The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail.The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.
Summary The neuronal synapse is underpinned by a large and diverse proteome but the molecular evidence is spread across many primary datasets. These data were recently curated into a single dataset describing a landscape of ∼ 8000 proteins found in studies of mammalian synapses. Here we describe programmatic access to the dataset via the R/Bioconductor package Synaptome.db, which enables convenient and in-depth data analysis from within the Bioconductor environment. Synaptome.db allows users to obtain the respective gene information, e.g. subcellular localization, brain region, gene ontology, disease association and construct custom protein-protein interaction network models for gene sets and entire subcellular compartments. Availability and implementation The package Synaptome.db is part of Bioconductor since release 3.14, https://bioconductor.org/packages/release/data/annotation/html/synaptome.db.html, it is open source and available under the Artistic license 2.0. The development version is maintained on GitHub (https://github.com/lptolik/synaptome.db). Full documentation including examples is provided in the form of vignettes on the package webpage. Supplementary information Supplementary data are available at Bioinformatics Advances online.
A comprehensible representation of a molecular network is key to communicating and understanding scientific results in systems biology. The Systems Biology Graphical Notation (SBGN) has emerged as the main standard to represent such networks graphically. It has been implemented by different software tools, and is now largely used to communicate maps in scientific publications. However, learning the standard, and using it to build large maps, can be tedious. Moreover, SBGN maps are not grounded on a formal semantic layer and therefore do not enable formal analysis. Here, we introduce a new set of patterns representing recurring concepts encountered in molecular networks, called SBGN bricks. The bricks are structured in a new ontology, the Bricks Ontology (BKO), to define clear semantics for each of the biological concepts they represent. We show the usefulness of the bricks and BKO for both the template-based construction and the semantic annotation of molecular networks. The SBGN bricks and BKO can be freely explored and downloaded at sbgnbricks.org.
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