Kai-Tai Chang

Prevalence, Resistance Mechanisms, and Susceptibility of Multidrug-Resistant Bloodstream Isolates of Pseudomonas aeruginosa

ABSTRACT Pseudomonas aeruginosa is an important pathogen commonly implicated in nosocomial infections. The occurrence of multidrug-resistant (MDR) P. aeruginosa strains is increasing worldwide and limiting our therapeutic options. The MDR phenotype can be mediated by a variety of resistance mechanisms, and the corresponding relative biofitness is not well established. We examined the prevalence, resistance mechanisms, and susceptibility of MDR P. aeruginosa isolates (resistant to ≥3 classes of antipseudomonal agents [penicillins/cephalosporins, carbapenems, quinolones, and aminoglycosides]) obtained from a large, university-affiliated hospital. Among 235 nonrepeat bloodstream isolates screened between 2005 and 2007, 33 isolates (from 20 unique patients) were found to be MDR (crude prevalence rate, 14%). All isolates were resistant to carbapenems and quinolones, 91% were resistant to penicillins/cephalosporins, and 21% were resistant to the aminoglycosides. By using the first available isolate for each bacteremia episode (n = 18), 13 distinct clones were revealed by repetitive-element-based PCR. Western blotting revealed eight isolates (44%) to have MexB overexpression. Production of a carbapenemase (VIM-2) was found in one isolate, and mutations in gyrA (T83I) and parC (S87L) were commonly found. Growth rates of most MDR isolates were similar to that of the wild type, and two isolates (11%) were found to be hypermutable. All available isolates were susceptible to polymyxin B, and only one isolate was nonsusceptible to colistin (MIC, 3 mg/liter), but all isolates were nonsusceptible to doripenem (MIC, >2 mg/liter). Understanding and continuous monitoring of the prevalence and resistance mechanisms of MDR P. aeruginosa would enable us to formulate rational treatment strategies to combat nosocomial infections.

Quantitative Assessment of Combination Antimicrobial Therapy against Multidrug-Resistant Acinetobacter baumannii

ABSTRACT Treatment of multidrug-resistant bacterial infections poses a therapeutic challenge to clinicians; combination therapy is often the only viable option for multidrug-resistant infections. A quantitative method was developed to assess the combined killing abilities of antimicrobial agents. Time-kill studies (TKS) were performed using a multidrug-resistant clinical isolate of Acinetobacter baumannii with escalating concentrations of cefepime (0 to 512 mg/liter), amikacin (0 to 256 mg/liter), and levofloxacin (0 to 64 mg/liter). The bacterial burden data in single and combined (two of the three agents with clinically achievable concentrations in serum) TKS at 24 h were mathematically modeled to provide an objective basis for comparing various antimicrobial agent combinations. Synergy and antagonism were defined as interaction indices of <1 and >1, respectively. A hollow-fiber infection model (HFIM) simulating various clinical (fluctuating concentrations over time) dosing exposures was used to selectively validate our quantitative assessment of the combined killing effect. Model fits in all single-agent TKS were satisfactory (r2 > 0.97). An enhanced combined overall killing effect was seen in the cefepime-amikacin combination (interactive index, 0.698; 95% confidence interval [CI], 0.675 to 0.722) and the cefepime-levofloxacin combination (interactive index, 0.929; 95% CI, 0.903 to 0.956), but no significant difference in the combined overall killing effect for the levofloxacin-amikacin combination was observed (interactive index, 0.994; 95% CI, 0.982 to 1.005). These assessments were consistent with observations in HFIM validation studies. Our method could be used to objectively rank the combined killing activities of two antimicrobial agents when used together against a multidrug-resistant A. baumannii isolate. It may offer better insights into the effectiveness of various antimicrobial combinations and warrants further investigations.

Uptake of Polymyxin B into Renal Cells

ABSTRACT Polymyxin B is increasingly used as a treatment of last resort against multidrug-resistant Gram-negative infections. Using a mammalian kidney cell line, we demonstrated that polymyxin B uptake into proximal tubular epithelial cells was saturable and occurred primarily through the apical membrane, suggesting the involvement of transporters in the renal uptake of polymyxin B. Megalin might play a role in the uptake and accumulation of polymyxin B into renal cells.

Impact of AmpC overexpression on outcomes of patients with Pseudomonas aeruginosa bacteremia

AmpC overexpression (AmpC++) is a significant mechanism of beta-lactam resistance in Pseudomonas aeruginosa, but its impact on clinical outcomes is not well established. To examine the influence of AmpC++ on clinical outcomes of patients with P. aeruginosa bacteremia, we screened all bloodstream P. aeruginosa isolates obtained from 2003 to 2006 for AmpC++. Demographics and outcomes were retrospectively compared between patients with P. aeruginosa bacteremia caused by AmpC++ and pan-susceptible strains (wild-type controls). Of the 263 isolates screened, 63 (24.0%) were nonsusceptible to ceftazidime. Clinical data of 42 AmpC++ isolates from 21 patients were compared with 33 control patients. The 2 groups were similar in sex and race. Patients in the AmpC++ group was more likely to receive inappropriate empiric antibiotics (odds ratio [OR] = 67.5; 95% confidence interval [CI], 6.3-720.0) and experience microbiologic persistence (OR = 12.2; 95% CI, 1.7-87.7). In institutions with a high prevalence of AmpC++, empiric therapy with agents with activity against AmpC++ strains may be warranted.

Impact of recA on Levofloxacin Exposure-Related Resistance Development

ABSTRACT Genetic mutations are one of the major mechanisms by which bacteria acquire drug resistance. One of the known mechanisms for inducing mutations is the SOS response system. We investigated the effect of disrupting recA, an inducer of the SOS response, on resistance development using an in vitro hollow-fiber infection model. A clinical Staphylococcus aureus isolate and a laboratory wild-type strain of Escherichia coli were compared to their respective recA-deleted isogenic daughter isolates. Approximately 2 × 105 CFU/ml of bacteria were subjected to escalating levofloxacin exposures for up to 120 h. Serial samples were obtained to ascertain simulated drug exposures and total and resistant bacterial burdens. Quinolone resistance determining regions of gyrA and grlA (parC for E. coli) in levofloxacin-resistant isolates were sequenced to confirm the mechanism of resistance. The preexposure MICs of the recA-deleted isolates were 4-fold lower than those of their respective parents. In S. aureus, a lower area under the concentration-time curve over 24 h at steady state divided by the MIC (AUC/MIC) was required to suppress resistance development in the recA-deleted mutant (an AUC/MIC of >23 versus an AUC/MIC of >32 was necessary in the mutant versus the parent isolate, respectively), and a prominent difference in the total bacterial burden was observed at 72 h. Using an AUC/MIC of approximately 30, E. coli resistance emergence was delayed by 24 h in the recA-deleted mutant. Diverse mutations in gyrA were found in levofloxacin-resistant isolates recovered. Disruption of recA provided additional benefits apart from MIC reduction, attesting to its potential role for pharmacologic intervention. The clinical relevance of our findings warrants further investigations.

Modeling of Microbial Population Responses to Time-Periodic Concentrations of Antimicrobial Agents

We present the development and first experimental validation of a mathematical modeling framework for predicting the eventual response of heterogeneous (distributed-resistance) microbial populations to antimicrobial agents at time-periodic (hence pharmacokinetically realistic) concentrations. Our mathematical model predictions are validated in a hollow-fiber in vitro experimental infection model. They are in agreement with the threshold levofloxacin exposure necessary to suppress resistance development of Pseudomonas aeruginosa in a murine thigh infection model. Predictions made by the proposed mathematical modeling framework can offer guidance for targeted testing of promising regimens. This can aid the development and clinical use of antimicrobial agents that combat microbial resistance.

Quantitative Impact of Neutrophils on Bacterial Clearance in a Murine Pneumonia Model

ABSTRACT The rapid increase in the prevalence of antibiotic-resistant pathogens is a global problem that has challenged our ability to treat serious infections. Currently, clinical decisions on treatment are often based on in vitro susceptibility data. The role of the immune system in combating bacterial infections is unequivocal, but it is not well captured quantitatively. In this study, the impact of neutrophils on bacterial clearance was quantitatively assessed in a murine pneumonia model. In vitro time-growth studies were performed to determine the growth rate constants of Acinetobacter baumannii ATCC BAA 747 and Pseudomonas aeruginosa PAO1. The absolute neutrophil count in mice resulting from different cyclophosphamide preparatory regimens was determined. The dynamic change of bacterial (A. baumannii BAA 747) burden in mice with graded immunosuppression over 24 h was captured by a mathematical model. The fit to the data was satisfactory (r2 = 0.945). The best-fit maximal kill rate (Kk) of the bacterial population by neutrophils was 1.743 h−1, the number of neutrophils necessary for 50% maximal killing was 190.8/μl, and the maximal population size was 1.8 × 109 CFU/g, respectively. Using these model parameter estimates, the model predictions were subsequently validated by the bacterial burden change of P. aeruginosa PAO1 at 24 h. A simple mathematical model was proposed to quantify the contribution of neutrophils to bacterial clearance and predict the bacterial growth/suppression in animals. Our results provide a novel framework to link in vitro and in vivo information and may be used to improve clinical treatment of bacterial infections.

Killing of Escherichia coli by β-lactams at different inocula☆

Escherichia coli is a common pathogen implicated in intra-abdominal infections; a heavy bacterial burden is often encountered, and the clinical utility of beta-lactams may be limited by the inoculum effect. We examined the impact of a high inoculum on the bactericidal activity of various beta-lactams against E. coli. Two wild-type, an extended-spectrum beta-lactamase-producing, and a plasmid-mediated AmpC-producing strains, were used. Clinically achievable concentrations of piperacillin/tazobactam, ceftriaxone, and ertapenem were investigated. Viable bacterial burden was serially determined for 24 h by quantitative culture. All 3 beta-lactams demonstrated significant killing against the standard inoculum (10(5) CFU/mL) of susceptible strains. However, the activity of piperacillin/tazobactam was drastically reduced with 10(8) CFU/mL of bacteria. Ertapenem was the least affected by the inoculum effect in all strains. Our results suggest that different beta-lactam subclasses have a distinct killing profile against a dense E. coli population. Comparative in vivo/clinical investigations are warranted to validate our findings.

Pharmacodynamics of moxifloxacin against a high inoculum of Escherichia coli in an in vitro infection model

OBJECTIVES Escherichia coli is the leading bacterial species implicated in intra-abdominal infections. In these infections a high bacterial burden with pre-existing resistant mutants are likely to be encountered and resistance could be amplified with suboptimal dosing. Our objective was to investigate the pharmacodynamics of moxifloxacin against a high inoculum of E. coli using an in vitro hollow fibre infection model (HFIM). METHODS Three wild-type strains of E. coli (ATCC 25922, MG1655 and EC28044) were studied by exposing approximately 2 x 10(8) cfu/mL (20 mL) to escalating dosing regimens of moxifloxacin (ranging from 30 to 400 mg, once daily). Serial samples were obtained from HFIM over 120 h to enumerate the total and resistant subpopulation. Quinolone resistance-determining regions of gyrA and parC of resistant isolates were sequenced to confirm the mechanism of resistance. RESULTS The pre-exposure MIC of the three wild-type strains was 0.0625 mg/L. Simulated moxifloxacin concentration profiles in HFIM were satisfactory (r(2) >or= 0.94). Placebo experiments revealed natural mutants, but no resistance amplification. Regrowth and resistance amplification was observed between 30 mg/day (AUC/MIC = 47) and 80 mg/day dose (AUC/MIC = 117). Sustained bacterial suppression was achieved at >or=120 mg/day dose (AUC/MIC = 180). Point mutations in gyrA (D87G or S83L) were detected in resistant isolates. CONCLUSIONS Our results suggest that suboptimal dosing may facilitate resistance amplification in a high inoculum of E. coli. The clinical dose of moxifloxacin (400 mg/day) was adequate to suppress resistance development in three wild-type strains. Clinical relevance of these findings warrants further in vivo investigation.

Mathematical Modeling To Characterize the Inoculum Effect

ABSTRACT Killing by beta-lactams is well known to be reduced against a dense bacterial population, commonly known as the inoculum effect. However, the underlying mechanism of this phenomenon is not well understood. We proposed a semimechanistic mathematical model to account for the reduced in vitro killing observed. Time-kill studies were performed with 4 baseline inocula (ranging from approximately 1 × 105 to 1 × 108 CFU/ml) of Escherichia coli ATCC 25922 (MIC, 2 mg/liter). Constant but escalating piperacillin concentrations used ranged from 0.25× to 256× MIC. Serial samples were taken over 24 h to quantify viable bacterial burden, and all the killing profiles were mathematically modeled. The inoculum effect was attributed to a reduction of effective drug concentration available for bacterial killing, which was expressed as a function of the baseline inoculum. Biomasses associated with different inocula were examined using a colorimetric method. Despite identical drug-pathogen combinations, the baseline inoculum had a significant impact on bacterial killing. Our proposed mathematical model was unbiased and reasonable in capturing all 28 killing profiles collectively (r2 = 0.88). Biomass was found to be significantly more after 24 h with a baseline inoculum of 1 × 108 CFU/ml, compared to one where the initial inoculum was 1 × 105 CFU/ml (P = 0.002). Our results corroborated previous observations that in vitro killing by piperacillin was significantly reduced against a dense bacterial inoculum. This phenomenon can be reasonably captured by our proposed mathematical model, and it may improve prediction of bacterial response to various drug exposures in future investigations.