Acinetobacter baumannii (American Type Culture Collection strain 19606) acquires mutations in the pmrB gene during the in vitro development of resistance to colistin. The colistin-resistant strain has lower affinity for colistin, reduced in vivo fitness (competition index, .016), and decreased virulence, both in terms of mortality (0% lethal dose_, 6.9 vs 4.9 log colony-forming units) and survival in a mouse model of peritoneal sepsis. These results may explain the low incidence and dissemination of colistin resistance in A. baumannii in clinical settings.

Acinetobacter baumannii causes pneumonias, bacteremias, and skin and soft tissue infections, primarily in the hospitalized setting. The incidence of infections caused by A. baumannii has increased dramatically over the last 30 years, while at the same time the treatment of these infections has been complicated by the emergence of antibiotic-resistant strains. Despite these trends, no vaccines or antibody-based therapies have been developed for the prevention of A. baumannii infection. In this study, an outer membrane complex vaccine consisting of multiple surface antigens from the bacterial membrane of A. baumannii was developed and tested in a murine sepsis model. Immunization elicited humoral and cellular responses that were able to reduce postinfection bacterial loads, reduce postinfection proinflammatory cytokine levels in serum, and protect mice from infection with human clinical isolates of A. baumannii . A single administration of the vaccine was able to elicit protective immunity in as few as 6 days postimmunization. In addition, vaccine antiserum was used successfully to therapeutically rescue naïve mice with established infection. These results indicate that prophylactic vaccination and antibody-based therapies based on an outer membrane complex vaccine may be viable approaches to preventing the morbidity and mortality caused by this pathogen.

There are currently no defined optimal therapies available for multidrug-resistant (MDR) Acinetobacter baumannii infections. We evaluated the efficacy of rifampin, imipenem, sulbactam, colistin, and their combinations against MDR A. baumannii in experimental pneumonia and meningitis models. The bactericidal in vitro activities of rifampin, imipenem, sulbactam, colistin, and their combinations were tested using time-kill curves. Murine pneumonia and rabbit meningitis models were evaluated using the A. baummnnii strain Ab1327 (with MICs for rifampin, imipenem, sulbactam, and colistin of 4, 32, 32, and 0.5 mg/liter, respectively). Mice were treated with the four antimicrobials and their combinations. For the meningitis model, the efficacies of colistin, rifampin and its combinations with imipenem, sulbactam, or colistin, and of imipenem plus sulbactam were assayed. In the pneumonia model, compared to the control group, (i) rifampin alone, (ii) rifampin along with imipenem, sulbactam, or colistin, (iii) colistin, or (iv) imipenem plus sulbactam significantly reduced lung bacterial concentrations (10.6 ± 0.27 [controls] versus 3.05 ± 1.91, 2.07 ± 1.82, 2.41 ± 1.37, 3.4 ± 3.07, 6.82 ± 3.4, and 4.22 ± 2.72 log ₁₀ CFU/g, respectively [means ± standard deviations]), increased sterile blood cultures (0% versus 78.6%, 100%, 93.3%, 93.8%, 73.3%, and 50%), and improved survival (0% versus 71.4%, 60%, 46.7%, 43.8%, 40%, and 85.7%). In the meningitis model rifampin alone or rifampin plus colistin reduced cerebrospinal fluid bacterial counts (−2.6 and −4.4 log ₁₀ CFU/ml). Rifampin in monotherapy or with imipenem, sulbactam, or colistin showed efficacy against MDR A. baumannii in experimental models of pneumonia and meningitis. Imipenem or sulbactam may be appropriate for combined treatment when using rifampin.

The aim of this study was to improve the understanding of the pharmacokinetic-pharmacodynamic relationships of fosfomycin against extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli strains that have different fosfomycin MICs. Our methods included the use of a hollow fiber infection model with three clinical ESBL-producing E. coli strains. Human fosfomycin pharmacokinetic profiles were simulated over 4 days. Preliminary studies conducted to determine the dose ranges, including the dose ranges that suppressed the development of drug-resistant mutants, were conducted with regimens from 12 g/day to 36 g/day. The combination of fosfomycin at 4 g every 8 h (q8h) and meropenem at 1 g/q8h was selected for further assessment. The total bacterial population and the resistant subpopulations were determined. No efficacy was observed against the Ec42444 strain (fosfomycin MIC, 64 mg/liter) at doses of 12, 24, or 36 g/day. All dosages induced at least initial bacterial killing against Ec46 (fosfomycin MIC, 1 mg/liter). High-level drug-resistant mutants appeared in this strain in response to 12, 15, and 18 g/day. In the study arms that included 24 g/day, once or in a divided dose, a complete extinction of the bacterial inoculum was observed. The combination of meropenem with fosfomycin was synergistic for bacterial killing and also suppressed all fosfomycin-resistant clones of Ec2974 (fosfomycin MIC, 1 mg/liter). We conclude that fosfomycin susceptibility breakpoints (≤64 mg/liter according to CLSI [for E. coli urinary tract infections only]) should be revised for the treatment of serious systemic infections. Fosfomycin can be used to treat infections caused by organisms that demonstrate lower MICs and lower bacterial densities, although relatively high daily dosages (i.e., 24 g/day) are required to prevent the emergence of bacterial resistance. The ratio of the area under the concentration-time curve for the free, unbound fraction of fosfomycin versus the MIC ( f AUC/MIC) appears to be the dynamically linked index of suppression of bacterial resistance. Fosfomycin with meropenem can act synergistically against E. coli strains in preventing the emergence of fosfomycin resistance.

The aim of this study was to analyse the interplay among plasmid-mediated qnr genes, alone or in combination with multiple chromosomal-mediated fluoroquinolone (FQ) resistance determinants, susceptibility to FQs and bacterial fitness in an isogenic Escherichia coli collection. E. coli ATCC 25922 was used to modify or delete chromosomal genes. qnr genes were cloned into the pBK-CMV vector. The MICs of FQs were determined by microdilution. Mutant prevention concentration and frequency of mutants were evaluated. Bacterial fitness was analysed using ΔlacZ system competition assays using in vitro and in vivo models. The relationships between the number of resistance mutations and bacterial fitness were complex. With specific combinations of resistance mechanisms the addition of a new resistance mutation was shown to improve bacterial fitness. qnrA1 caused a decrease in fitness (7%–21%) while qnrS1 caused an increase in fitness (9%–21%) when combined with chromosomal mutations. We identified susceptible triple mutants in which the acquisition of a fourth resistance mutation significantly increased fitness and at the same time reached the clinical resistance level (the acquisition of qnrS1 in a S83L + D87N + ΔmarR genetic background). A strong correlation with the production of reactive oxygen species, as well as changes in susceptibility, was observed following treatment with ciprofloxacin. Our data indicate that there may be critical stages (depending on the genotype) in resistance development, including chromosomal- and plasmid-mediated mechanisms, at which some low-fitness mutants below the resistance breakpoint are able to evolve clinical resistance with just one or two mutations, and show increased fitness.

Suppression of the SOS response has been postulated as a therapeutic strategy for potentiating antimicrobial agents. We aimed to evaluate the impact of its suppression on reversing resistance using a model of isogenic strains of Escherichia coli representing multiple levels of quinolone resistance. E. coli mutants exhibiting a spectrum of SOS activity were constructed from isogenic strains carrying quinolone resistance mechanisms with susceptible and resistant phenotypes. Changes in susceptibility were evaluated by static (MICs) and dynamic (killing curves or flow cytometry) methodologies. A peritoneal sepsis murine model was used to evaluate in vivo impact. Suppression of the SOS response was capable of resensitizing mutant strains with genes encoding three or four different resistance mechanisms (up to 15-fold reductions in MICs). Killing curve assays showed a clear disadvantage for survival (Δlog ₁₀ CFU per milliliter [CFU/ml] of 8 log units after 24 h), and the in vivo efficacy of ciprofloxacin was significantly enhanced (Δlog ₁₀ CFU/g of 1.76 log units) in resistant strains with a suppressed SOS response. This effect was evident even after short periods (60 min) of exposure. Suppression of the SOS response reverses antimicrobial resistance across a range of E. coli phenotypes from reduced susceptibility to highly resistant, playing a significant role in increasing the in vivo efficacy. IMPORTANCE The rapid rise of antibiotic resistance in bacterial pathogens is now considered a major global health crisis. New strategies are needed to block the development of resistance and to extend the life of antibiotics. The SOS response is a promising target for developing therapeutics to reduce the acquisition of antibiotic resistance and enhance the bactericidal activity of antimicrobial agents such as quinolones. Significant questions remain regarding its impact as a strategy for the reversion or resensitization of antibiotic-resistant bacteria. To address this question, we have generated E. coli mutants that exhibited a spectrum of SOS activity, ranging from a natural SOS response to a hypoinducible or constitutively suppressed response. We tested the effects of these mutations on quinolone resistance reversion under therapeutic concentrations in a set of isogenic strains carrying different combinations of chromosome- and plasmid-mediated quinolone resistance mechanisms with susceptible, low-level quinolone resistant, resistant, and highly resistant phenotypes. Our comprehensive analysis opens up a new strategy for reversing drug resistance by targeting the SOS response.