METHODS: In total, 7541 organisms causing documented infections were consecutively collected in 66 centres in 33 countries, excluding the USA. Susceptibility testing was performed by broth microdilution. Isolates displaying linezolid MIC results of ≥4 mg/L were molecularly characterized.
RESULTS: Linezolid inhibited all Staphylococcus aureus at ≤2 mg/L, with MIC50 results of 1 mg/L, regardless of methicillin resistance. A similar linezolid MIC50 result (i.e. 0.5 mg/L) was observed against CoNS, with the vast majority of isolates (99.4%) also inhibited at ≤2 mg/L. Six CoNS that exhibited elevated linezolid MIC values were found to contain alterations in the 23S rRNA and/or L3 ribosomal protein. Linezolid exhibited consistent modal MIC and MIC50 results (1 mg/L) against enterococci, regardless of species or vancomycin resistance. Three Enterococcus faecalis from Galway and Dublin (Ireland) and Kelantan (Malaysia) showed MIC results of 4 to 8 mg/L and carried optrA. All Streptococcus pneumoniae, viridans-group streptococci and β-haemolytic streptococci were inhibited by linezolid at ≤2, ≤2 and ≤1 mg/L, respectively, with equivalent MIC90 results (1 mg/L for all groups).
CONCLUSIONS: These results document the continued long-term and stable in vitro potency of linezolid and reveal a limited number of isolates with decreased susceptibility to linezolid (i.e. MIC ≥4 mg/L). The latter isolates primarily showed mutations in the 23S rRNA gene and/or L3 protein, but cfr was not detected. Moreover, this study shows that isolates carrying the newly described ABC transporter optrA are not restricted to China.
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.