[General principles of antibiotic resistance evolution in bacteria (review of literature).]
Nataliia Valerievna DavidovichN N KukalevskayaE N BashilovaT A BazhukovaPublished in: Klinicheskaia laboratornaia diagnostika (2020)
Currently, the impact of antibiotic resistance on human health is a worldwide problem and its study is of great interest from a molecular genetic, environmental and clinical view-point. This review summarizes the latest data about antibiotic resistance, the classification of microorganisms as sensitive and resistant to the action of antibiotics, reveals the concept of minimum inhibitory concentration from modern positions. The resistance of microorganisms to antibacterial agents can be intrinsic and acquired, as well as being one of the examples of evolution that are currently available for study. Modern methods of whole-genome sequencing and complex databases of nucleotide-tagged libraries give an idea of the multifaceted nature of the mechanisms of intrinsic resistance to antibiotics and are able to provide information on genes encoding metabolic enzymes and proteins that regulate the basic processes of the physiology of bacteria. The article describes the main ways of spreading the resistance of microorganisms, reflects the concepts of "founder effect" and the fitness cost of bacteria, which underlie the emergence and evolution of antibiotic resistance. It is shown that the origin of antibiotic resistance genes that human pathogens currently possess can be traced by studying the surrounding not only clinical, but also non-clinical (ecological) habitats. As well as microorganisms of the surrounding ecosystems are the donors of resistance genes in horizontal gene transfer.
Keyphrases
- human health
- genome wide
- risk assessment
- climate change
- antibiotic resistance genes
- endothelial cells
- machine learning
- physical activity
- healthcare
- copy number
- genome wide identification
- deep learning
- body composition
- big data
- multidrug resistant
- anti inflammatory
- single molecule
- artificial intelligence
- social media
- bioinformatics analysis
- essential oil
- kidney transplantation