Interaction of antibacterial compounds with RND efflux pumps in Pseudomonas aeruginosa

Gram-negative bacteria characteristically are surrounded by an additional membrane layer, the outer membrane. Although outer membrane components often play important roles in the interaction of symbiotic or pathogenic bacteria with their host organisms, the major role of this membrane must usually be to serve as a permeability barrier to prevent the entry of noxious compounds and at the same time to allow the influx of nutrient molecules. This review summarizes the development in the field since our previous review (H. Nikaido and M. Vaara, Microbiol. Rev. 49:1-32, 1985) was published. With the discovery of protein channels, structural knowledge enables us to understand in molecular detail how porins, specific channels, TonB-linked receptors, and other proteins function. We are now beginning to see how the export of large proteins occurs across the outer membrane. With our knowledge of the lipopolysaccharide-phospholipid asymmetric bilayer of the outer membrane, we are finally beginning to understand how this bilayer can retard the entry of lipophilic compounds, owing to our increasing knowledge about the chemistry of lipopolysaccharide from diverse organisms and the way in which lipopolysaccharide structure is modified by environmental conditions.

Combined quantum-mechanics/molecular-mechanics (QM/MM) approaches have become the method of choice for modeling reactions in biomolecular systems. Quantum-mechanical (QM) methods are required for describing chemical reactions and other electronic processes, such as charge transfer or electronic excitation. However, QM methods are restricted to systems of up to a few hundred atoms. However, the size and conformational complexity of biopolymers calls for methods capable of treating up to several 100,000 atoms and allowing for simulations over time scales of tens of nanoseconds. This is achieved by highly efficient, force-field-based molecular mechanics (MM) methods. Thus to model large biomolecules the logical approach is to combine the two techniques and to use a QM method for the chemically active region (e.g., substrates and co-factors in an enzymatic reaction) and an MM treatment for the surroundings (e.g., protein and solvent). The resulting schemes are commonly referred to as combined or hybrid QM/MM methods. They enable the modeling of reactive biomolecular systems at a reasonable computational effort while providing the necessary accuracy.

To describe the frequency of selected antimicrobial resistance patterns among pathogens causing device-associated and procedure-associated healthcare-associated infections (HAIs) reported by hospitals in the National Healthcare Safety Network (NHSN). Data are included on HAIs (ie, central line-associated bloodstream infections, catheter-associated urinary tract infections, ventilator-associated pneumonia, and surgical site infections) reported to the Patient Safety Component of the NHSN between January 2006 and October 2007. The results of antimicrobial susceptibility testing of up to 3 pathogenic isolates per HAI by a hospital were evaluated to define antimicrobial-resistance in the pathogenic isolates. The pooled mean proportions of pathogenic isolates interpreted as resistant to selected antimicrobial agents were calculated by type of HAI and overall. The incidence rates of specific device-associated infections were calculated for selected antimicrobial-resistant pathogens according to type of patient care area; the variability in the reported rates is described. Overall, 463 hospitals reported 1 or more HAIs: 412 (89%) were general acute care hospitals, and 309 (67%) had 200-1,000 beds. There were 28,502 HAIs reported among 25,384 patients. The 10 most common pathogens (accounting for 84% of any HAIs) were coagulase-negative staphylococci (15%), Staphylococcus aureus (15%), Enterococcus species (12%), Candida species (11%), Escherichia coli (10%), Pseudomonas aeruginosa (8%), Klebsiella pneumoniae (6%), Enterobacter species (5%), Acinetobacter baumannii (3%), and Klebsiella oxytoca (2%). The pooled mean proportion of pathogenic isolates resistant to antimicrobial agents varied significantly across types of HAI for some pathogen-antimicrobial combinations. As many as 16% of all HAIs were associated with the following multidrug-resistant pathogens: methicillin-resistant S. aureus (8% of HAIs), vancomycin-resistant Enterococcus faecium (4%), carbapenem-resistant P. aeruginosa (2%), extended-spectrum cephalosporin-resistant K. pneumoniae (1%), extended-spectrum cephalosporin-resistant E. coli (0.5%), and carbapenem-resistant A. baumannii, K. pneumoniae, K. oxytoca, and E. coli (0.5%). Nationwide, the majority of units reported no HAIs due to these antimicrobial-resistant pathogens.