Background. Inflammatory periodontal diseases, including chronic periodontitis, are accompanied by a chronic persisting inflammatory process. The latter process and biofilm-forming potential are the factors that contribute to the formation of antibiotic-resistant microorganism strains. The purpose of our work was to study the biofilm-forming ability of antibiotic-resistant biofilm-forming Staphylococcus genus bacteria isolated from the oral cavities of patients suffering from periodontitis, and check the presence of the genes associated with biofilm formation in these bacteria. Material and methods. Isolates were obtained from patients suffering from chronic periodontitis using differentially diagnostic nutrient media. Chemotaxonomic identification of the antibiotic-resistant isolates was performed on the Microflex LT device. Biofilm-forming potential was studied in plastic Petri dishes by spectrophotometric method. The antibiotic sensitivity of the bacteria and microscopic fungi was identified by the disc diffusion method. The presence of icaA, icaD, icaC, icaB, agrA, srtA genes was detected in two multiplex polymerase chain reactions (mPCR). 16S rRNA gene and icaR genes were amplified in a separate PCR. Results. Opportunistic microbial associations dominate in the microbiom of the oral cavity under conditions of periodontitis; besides, in the majority of cases, Staphylococcus genus bacteria were present in associations. In 73 % (131/180) of cases, bacte ria from Staphylococcus genus represented by six species-S. aureus, S. haemolyticus, S. saprophyticus, S. epidermidis, S. xelosus, and S. hominis were isolated from the nidus during the inflammatory process. From the oral cavities of the patients with inflammatory periodontitis, 51 biofilm-forming strains of S. aureus, 29 strains of S. haemolyticus, 12 strains of S. saprophyticus, and 12 strains of S. epidermidis were isolated. It was established that antibiotic-resistant isolates of S. aureus possess the genetic determinants which are now believed to be connected with icaA, icaC, icaB icaA, icaR, agrA, and srtA biofilm-forming potential. Two non-biofilm forming strains of S. aureus were proven to lack the genes responsible for the biofilm-forming ability. Conclusion: It has been established that microbial associations with a prevailing share of Staphylococcus genus bacteria, most of which have a biofilm-forming potential, dominate in the microbiom of the oral cavity under conditions of periodontitis.
Background. An excessive use of antibiotics in human and veterinary medicine contributes to the additional selection pressure on microorganisms and leads to the rapid spread of dangerous microorganisms with an increased ability to resist numerous classes of antibiotics. Aquatic ecosystems are among the main resistance genes pools, and therefore should be subject to mandatory control. Apparently, the spread of antibi oticresistant microorganisms depends not only on the concentration of antibiotics en tering water bodies with wastewaters, but also on other qualitative characteristics of the aquatic environment. The aim of this work was to determine the correlation between the content of heavy metals (Cu, Ni, Zn, Cr) and nitrogen compounds (NO 3 , NO 2 and NH 4) in water and the distribution of antibiotic resistant microorganisms in research sites on the Uzh River (Ukraine) that are affected by anthropogenic impact. Based on our seasonal moni toring during 2016-2017, which included determining the content of nitrogen compounds and heavy metals in the research sites, and as a result of the study on the microbiocenosis structure with a subsequent determination of antibiotic sensitivity of the dominant strains isolated from water samples, we conducted analysis of the correlation between the concentrations of these substances and the distribution of antibiotic resistant strains. This enabled us to identify the potential factors that contribute to the deve lopment of antibiotic resistance in microorganisms. Material and methods. The relationship between the chemical parameters and the percentage of antibioticresistant microorganisms was determined using the linear Pearson's correlation coefficient (r). Statistical data processing was performed using the software package "Microsoft Excel". Results with a pvalue less than 0.05 (р<0.05) were considered statistically significant.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.