Multiparametric determination of genes and their point mutations for identification of beta-lactamases

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Abstract

More than half of all currently used antibiotics belong to the beta-lactam group, but their clinical effectiveness is severely limited by antibiotic resistance of microorganisms that are the causative agents of infectious diseases. Several mechanisms for the resistance of Enterobacteriaceae have been established, but the main one is the enzymatic hydrolysis of the antibiotic by specific enzymes called beta-lactamases. Beta-lactamases represent a large group of genetically and function-ally different enzymes of which extended-spectrum beta-lactamases (ESBLs) pose the greatest threat. Due to the plasmid localization of the encoded genes, the distribution of these enzymes among the pathogens increases every year. Among ESBLs the most widespread and clinically relevant are class A ESBLs of TEM, SHV, and CTX-M types. TEM and SHV type ESBLs are derived from penicillinases TEM-1, TEM-2, and SHV-1 and are characterized by several single amino acid substitutions. The extended spectrum of substrate specificity for CTX-M beta-lactamases is also associated with the emergence of single mutations in the coding genes. The present review describes various molecular-biological methods used to identify determinants of antibiotic resistance. Particular attention is given to the method of hybridization analysis on microarrays, which allows simultaneous multiparametric determination of many genes and point mutations in them. A separate chapter deals with the use of hybridization analysis on microarrays for genotyping of the major clinically significant ESBLs. Specificity of mutation detection by means of hybridization analysis with different detection techniques is compared. © 2010 Pleiades Publishing, Ltd.

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Rubtsova, M. Y., Ulyashova, M. M., Bachmann, T. T., Schmid, R. D., & Egorov, A. M. (2010). Multiparametric determination of genes and their point mutations for identification of beta-lactamases. Biochemistry (Moscow). Maik Nauka Publishing / Springer SBM. https://doi.org/10.1134/S0006297910130080

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