RESULTS: Unique and specific primer pairs were designed to amplify the 8 genes. The specificity of the primers was confirmed by DNA sequencing of the nanoplex PCR products and BLAST analysis. The sensitivity and specificity of V-BiA-RE nanoplex PCR assay was evaluated against the conventional culture method. The analytical sensitivity of the assay was found to be 1 ng at the DNA level while the analytical specificity was evaluated with 43 reference enterococci and non-enterococcal strains and was found to be 100%. The diagnostic accuracy was determined using 159 clinical specimens, which showed that 97% of the clinical isolates belonged to E. faecalis, of which 26% showed the HLGR genotype, but none were vancomycin resistant. The presence of an internal control in the V-BiA-RE nanoplex PCR assay helped us to rule out false negative cases.
CONCLUSION: The nanoplex PCR assay is robust and can give results within 4 hours about the 8 genes that are essential for the identification of the most common Enterococcus spp. and their antibiotic sensitivity pattern. The PCR assay developed in this study can be used as an effective surveillance tool to study the prevalence of enterococci and their antibiotic resistance pattern in hospitals and farm animals.
DATA DESCRIPTION: We tested the effects of SdsR and SdsRv2 on fluoroquinolone resistance in S. sonnei in vivo. SdsRv2 is a synthetic version which promotes higher binding stability to tolC mRNA. Overexpression of either SdsR or SdsRv2 lowers the expression of tolC mRNA. Interestingly, SdsR and SdsRv2 promote the growth of S. sonnei in the presence of a sub-inhibitory concentration of norfloxacin. Mutant carrying SdsRv2 showed the highest growth advantage. This phenotype is opposite to the effect of SdsR reported in E. coli. This study is an example that demonstrates the difference in the phenotypic effect of a highly conserved sRNA in two closely related bacteria.
PATIENTS AND METHODS: With concern over its rising microbial resistance, we explored the association of empiric antibiotics choices with the hospital outcomes of patients treated for microbial proven K. pneumoniae pneumonia in an urban-based teaching hospital.
RESULTS: In 313 eligible cases reviewed retrospectively, hospital mortality and requirement for ventilation were 14.3% and 10.8% respectively. Empiric regimes that had in vitro resistance to at least one empiric antibiotic (n = 90) were associated with higher hospital mortality (23.3% vs. 10.8%, P = 0.004) with risk increased by about two-fold [Odds ratio (OR), 2.5; 95% confidence interval (CI), 1.3 to 4.8]. Regimes (n = 84) other than the commonly recommended "standard" regimes (a beta-lactam stable antibiotic with or without a acrolide) were associated with higher ventilation rates (16.7% vs. 8.8%, P = 0.047) with similar increased risk [OR, 2.0; 95% CI, 1.0 to 4.3].
CONCLUSIONS: Our findings reiterate the clinical relevance of in vitro microbial resistance in adult K. pneumoniae pneumonia and support empiric regimes that contain beta-lactam stable antibiotics.
METHODOLOGY/PRINCIPAL FINDINGS: In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery.
CONCLUSION/SIGNIFICANCE: The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial structure is a key factor, which helps bacteria to survive and to adapt to changed environmental conditions.